Abstract
A species’ potential distribution can be modelled adequately only if no factor other than habitat availability affects its occurrences. Space use by stone marten Martes foina is likely to be affected by interspecific competition with the strictly related pine marten Martes martes, the latter being able to outcompete the first species in forested habitats. Hence, to point out the environmental factors which determine the distribution and density of the stone marten, a relatively understudied mesocarnivore, we applied two non-invasive survey methods, camera-trapping and faecal-DNA based genetic analysis, in an Alpine area where the pine marten was deemed to be absent (Val Grande National Park N Italy). Camera trapping was conducted from October 2014 to November 2015, using up to 27 cameras. Marten scats were searched for between July and November 2015 and, to assess density, in spring 2017. Species identification was accomplished by a PCR-RFLP method, while 17 autosomal microsatellites were used for individual identification. The stone marten occurred in all available habitats (83% of trapping sites and 73.2% of scats); nonetheless, habitat suitability, as assessed using MaxEnt, depended on four major land cover variables—rocky grasslands, rocks and debris, beech forests and chestnut forests—, martens selecting forests and avoiding open rocky areas. Sixteen individuals were identified, of which 14 related to each other, possibly forming six different groups. Using capwire estimators, density was assessed as 0.95 (0.7–1.3) ind/km2. In the study area, the widespread stone marten selected forested areas, attaining density values like those reported for the pine marten in northern Europe and suggesting that patterns of habitat selection may depend on the relative abundance of the two competing martens.
Highlights
Affecting ecosystem function, structure and dynamics, mesocarnivores play important roles in natural communities and are considered sensitive indicators of environmental health and change in forested and aquatic habitats, wherever large carnivores have been driven to extinction by human interference (Buskirk and Zielinski 2003; Roemer et al 2009)
Following the reclassification analysis based on equal training sensitivity and specificity” threshold (ETSS) = 0.47, 63.9% of the study area resulted suitable for the stone marten (Fig. 5), which, according to univariate analysis, selected beech- and other deciduous forests, while avoided rocky and scree areas (Table 3). Associative modelling approaches, such as SDMs, which consider the target species locations to be representative of ideal habitat conditions, assess adequately the species potential distribution only if no other factor plays a major role in determining its occurrences (Gough and Rushton 2000)
If we assume that the frequency of occurrence of records is an index of the relative abundance of both species (Gese 2001; Carbone et al 2001), the stone marten stood out in terms of numbers
Summary
Structure and dynamics, mesocarnivores play important roles in natural communities and are considered sensitive indicators of environmental health and change in forested and aquatic habitats, wherever large carnivores have been driven to extinction by human interference (Buskirk and Zielinski 2003; Roemer et al 2009). Among the mustelid family, which largely contribute to the diversity of European mesocarnivores, the stone marten Martes foina has currently been understudied The stone marten is widespread through much of continental Europe and central Asia—from Portugal in the west as far as north-western China in the east (Proulx et al 2004)—, data on its spatial ecology are scarce To the best of our knowledge, density data are reported by only three available studies, conducted in either rural (Switzerland 0.7–2 ind/km2, Lachat Feller 1993; Germany: 2 adult and 1.5 juvenile ind/ km2, Herrmann 2004) or urban areas (4.7–5.8 ind/km2, Herr et al 2009) by means of radiotracking. Population density was similar to that recorded in rural Switzerland (0.96 ind/km2; Ronchi 2016), the REM has been demonstrated to largely underestimate marten density (Balestrieri et al 2016a)
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