Scale‐dependent environmental variables affecting red squirrel (<i>Sciurus vulgaris meridionalis</i>) distribution

Rima, P.C.; Cagnin, Mara; Aloise, Gaetano; Preatoni, Damiano; Wauters, Luc A.

doi:10.1080/11250000902766926

Cited by 11 publications

(7 citation statements)

References 47 publications

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“…Red squirrels prefer high canopy trees to build their middens ( Fig. 9 ), which agrees with what the literature elaborates about squirrel habitat choice for the red squirrel ( Kemp & Keith, 1970 ) as well as for the European red squirrel ( Rima et al, 2010 ; Flaherty, Lurz & Patenaude, 2014 ). The fact that squirrels give preference to dense ( Gurnell, 1984 ) or interlocking canopy to increase their foraging success and their escape possibilities from predators ( Elkins et al, 2018 ; Steele, 1998 ; Vahle & Patton, 1983 ; Smith, 1968a ) supports these outcomes.…”

Section: Discussionsupporting

confidence: 88%

High-resolution prediction of American red squirrel in Interior Alaska: a role model for conservation using open access data, machine learning, GIS and LIDAR

Robold

Huettmann

2021

PeerJ

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American red squirrels (Tamiasciurus hudsonicus) are small mammals that are abundantly distributed throughout North America. Urbanization in the Anthropocene is now a global process, and squirrels live in affected landscapes. This leads to squirrels adjusting to human developments. Not much is known about the distribution of squirrels and squirrel middens near humans, especially not in the subarctic and sub-urbanized regions. Although this species is hunted, there are no real publicly available distribution and abundance estimates nor management plans and bag limits for squirrels in Alaska or in the United States known by us, except the endangered Mt. Graham squirrel. In general, insufficient squirrel conservation research is carried out; they are underrepresented in research and its literature. To further the science-based management for such species, this study aims to generate the first digital open access workflow as a generic research template for small mammal work including the latest machine learning of open source and high-resolution LIDAR data in an Open Source Geographic Information System (QGIS) and ArcGIS. Machine learning has proven to be less modeler biased and improve accuracy of the analysis outcome, therefore it is the preferred approach. This template is designed to be rapid, simple, robust, generic and effective for being used by a global audience. As a unique showcase, here a squirrel midden survey was carried out for two years (2016 and 2017). These squirrel middens were detected in a research area of 45,5 hectares (0,455 km2) in downtown Fairbanks, interior boreal forest of Alaska, U.S. Transect distances were geo-referenced with a GPS and adjusted to the visual conditions to count all squirrel middens within the survey area. Different layers of proximity to humans and habitat characteristics were assembled using aerial imagery and LIDAR data (3D data needed for an arboreal species like the red squirrels) consisting of a 3 × 3 m resolution. The layer data was used to train a predictive distribution model for red squirrel middens with machine learning. The model showed the relative index of occurrence (RIO) in a map and identified canopy height, distance to trails, canopy density and the distance to a lake, together, as the strongest predictors for squirrel midden distribution whereas open landscape and disturbed areas are avoided. It is concluded that squirrels select for high and dense forests for middens while avoiding human disturbance. This study is able to present a machine learning template to easily and rapidly produce an accurate abundance prediction which can be used for management implications.

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Section: Discussionsupporting

confidence: 88%

High-resolution prediction of American red squirrel in Interior Alaska: a role model for conservation using open access data, machine learning, GIS and LIDAR

Robold

Huettmann

2021

PeerJ

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“…We emphasize four key-issues relevant for future studies: 1. We did not consider the quality or vegetation structure of forest patches, which is an important predictor in fragmented landscapes for many species including the hazel dormouse and the red squirrel (Van Apeldoorn, Celada & Nieuwenhuizen 1994;Bright & Morris 1996;Rima et al 2010). Part of the unexplained variance found in the first ranked model of both species could be explained by the quality of patches in the landscapes.…”

Section: Rodent Distribution In Fragmented Landscapes 159mentioning

confidence: 99%

“… We did not consider the quality or vegetation structure of forest patches, which is an important predictor in fragmented landscapes for many species including the hazel dormouse and the red squirrel (Van Apeldoorn, Celada & Nieuwenhuizen 1994; Bright & Morris 1996; Rima et al. 2010).…”

Section: Implications For the Management Of Landscapesmentioning

confidence: 99%

Independent effects of habitat loss, habitat fragmentation and structural connectivity on the distribution of two arboreal rodents

Mortelliti

Amori

Capizzi³

et al. 2010

Journal of Applied Ecology

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Summary 1.Habitat loss must be distinguished from habitat fragmentation so that appropriate conservation management can be applied. Few studies have evaluated the independent effects of habitat loss and habitat fragmentation on the distribution of vertebrates, and none has evaluated the independent effect of changes in structural connectivity. We carried out a landscape-scale experiment to assess the independent contribution of these three processes and to examine what landscape scale factors affect the distribution of two forest-dependent arboreal rodents: the hazel dormouse Muscardinus avellanarius and the red squirrel Sciurus vulgaris. 2. Habitat loss, rather than habitat fragmentation per se, was the major driver of distribution patterns for both species. As predicted, structural connectivity (hedgerow networks) played an important role in determining the distribution of the hazel dormouse, but not of the red squirrel. 3. Our models predict that long lengths of hedgerows (>30 km) are unlikely to increase the probability of occurrence of hazel dormouse in landscapes where there are low levels of forest cover (<5%-10%). 4. Synthesis and applications. Our empirical findings indicate that structural connectivity and habitat loss may have additive effects on vertebrate distribution. For the hazel dormouse, improving structural connectivity will be ineffective if the amount of forest cover in the landscape is less than 5-10%. The key message from this study is that resources should not be invested in landscape linkages until their efficacy for the given level of suitable habitat has been assessed.

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“…The squirrel selectivity at the landscape scale was further reinforced by the results of the models obtained with the map of vegetation associations, which showed a clear influence only for the red squirrel and indicated a preference for oak woods and coniferous reforestations. Even in a landscape naturally dominated by broadleaf species, where conifers covered less than the 2% of the study area, the squirrel confirms its preference for this element (Van Apeldoorn et al 1994;Rima et al 2010). Considering that in terms of landscape configuration, the most relevant factors were the length of shared perimeter between hedgerows and woods and the amount of woods, we can sustain the dominant role of landscape structure on occupancy patterns (Celada et al 1994).…”

Section: Discussionmentioning

confidence: 71%

Assessing environmental requirements effects on forest fragmentation sensitivity in two arboreal rodents

et al. 2013

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The study of the effect of habitat fragmentation on species that inhabit residual patches requires the investigation of the relationship existing between species distribution and landscape components. To understand which components of landscape mosaics are more influential for species’ persistence, we compared the distribution of two arboreal rodents proved to be sensitive to habitat fragmentation, the\ud hazel dormouse Muscardinus avellanarius and the red squirrel Sciurus vulgaris. Their occurrence in residual oak woods in central Italy was studied with nest-boxes and hair-tubes, developing a new method for hair analysis. Their distributions were analysed considering patch, matrix composition and configuration, and landscape vegetation variables. The two species showed a different degree of plasticity, with the squirrel being significantly more specialised at the landscape scale. The comparison of the two distribution patterns highlighted the influence of different ecological constraints and the existence of different strategies to cope with fragmentation. Patch size and patch attributes were generally weaker determinants of occurrence, compared to landscape metrics. The squirrel presence was significantly influenced by the presence of shared perimeter between hedgerows and woods and by the lack of isolation of the\ud residual patches, suggesting the use of several fragments to compensate the low habitat quality. Conversely the hazel dormouse seemed to be more affected by the internal management of the woods, and in particular by the mean DBH. Our results highlight how the recognition of the extrinsic constraints and the influence of multi-scale habitat selection may help guiding land use management, to ensure species conservation in profoundly exploited landscapes

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Scale‐dependent environmental variables affecting red squirrel (Sciurus vulgaris meridionalis) distribution

Cited by 11 publications

References 47 publications

High-resolution prediction of American red squirrel in Interior Alaska: a role model for conservation using open access data, machine learning, GIS and LIDAR

High-resolution prediction of American red squirrel in Interior Alaska: a role model for conservation using open access data, machine learning, GIS and LIDAR

Independent effects of habitat loss, habitat fragmentation and structural connectivity on the distribution of two arboreal rodents

Assessing environmental requirements effects on forest fragmentation sensitivity in two arboreal rodents

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