2022
DOI: 10.1038/s41598-022-08468-7
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Smartphone app reveals that lynx avoid human recreationists on local scale, but not home range scale

Abstract: Outdoor recreation is increasing and affects habitat use and selection by wildlife. These effects are challenging to study, especially for elusive species with large spatial requirements, as it is hard to obtain reliable proxies of recreational intensity over extensive areas. Commonly used proxies, such as the density of, or distance to, hiking paths, ignore outdoor recreation occurring on other linear feature types. Here we utilized crowdsourced data from the Strava training app to obtain a large-scale proxy … Show more

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Cited by 10 publications
(17 citation statements)
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“…In addition, responses by large carnivores to human pressures also might vary across spatial scales of habitat use (e.g., establishment of home ranges in the wider landscape vs. use of areas within a home range; Mayor et al 2009). For example, several studies have found carnivores to avoid human-caused mortality risks primarily at broader scales, while selecting mainly for higher resource availability at finer scales (Ripari et al 2022;Thorsen et al 2022). A better understanding of how human pressure shapes large carnivore habitat use across scales could provide important insights into their adaptive capacity and reveal opportunities and limitations for landscapes of coexistence where large carnivores and people co-occur sustainably (Oriol-Cotterill et al 2015).…”
Section: Introductionmentioning
confidence: 99%
“…In addition, responses by large carnivores to human pressures also might vary across spatial scales of habitat use (e.g., establishment of home ranges in the wider landscape vs. use of areas within a home range; Mayor et al 2009). For example, several studies have found carnivores to avoid human-caused mortality risks primarily at broader scales, while selecting mainly for higher resource availability at finer scales (Ripari et al 2022;Thorsen et al 2022). A better understanding of how human pressure shapes large carnivore habitat use across scales could provide important insights into their adaptive capacity and reveal opportunities and limitations for landscapes of coexistence where large carnivores and people co-occur sustainably (Oriol-Cotterill et al 2015).…”
Section: Introductionmentioning
confidence: 99%
“…To check for the reliability of these two categories in the field, we compared the daily attendance of hikers (number of hikers recorded on the trail) between 03:00 UTC and 23:00 UTC and the hour of first arrival for both temporal disturbance levels using an eco-counter (PYRO sensor Eco-Compteur, www.eco-compteur.com; 90 cm above ground) located on Armenaz trail (45°37'18.60" N, 6°13'2.53" E), on a subset of the study period ( 2016 Potential spatial exposure to hikers disturbance was evaluated within each female chamois home range using frequentation rates of the trails extracted from Strava Global Heatmap (Strava, 2022;www.strava.com, download date: 2022/03/09, data from the two previous years, see also Courbin et al, 2022 for a similar approach on this study site). Strava heatmap provides a value ranging from 0 for no attendance to 255 for the highest attendance for each pixel of the map and is a good proxy of relative human frequentation (Supporting information 2, see also Thorsen et al, 2022). The lowest value recorded for a trail pixel in our study site was 51, so we defined frequentation classes according to the quantiles of the [51; 255] distribution (i.e.…”
Section: Data Collectionmentioning
confidence: 99%
“…Potential spatial exposure to hikers disturbance was evaluated within each female chamois home range using frequentation rates of the trails extracted from Strava Global Heatmap (Strava, 2022;www.strava.com, download date: 2022/03/09, data from the two previous years, see also Courbin et al, 2022 for a similar approach on this study site). Strava heatmap provides a value ranging from 0 for no attendance to 255 for the highest attendance for each pixel of the map and is a good proxy of relative human frequentation (Supporting information 2, see also Thorsen et al, 2022). The lowest value recorded for a trail pixel in our study site was 51, so we defined frequentation classes according to the quantiles of the [51; 255] distribution (i.e.…”
Section: Data Collectionmentioning
confidence: 99%
“…This newly-developed index, ranging from 0 (no outdoor activity in the 20x20-m cell) to 1 (very high outdoor activity in the cell), is a single static representation of all aggregated, public activities uploaded to the Strava App. Importantly, the spatial patterns in outdoor activities do not change across years (23), making the index an effective representation of the volume of human activity in a given area (see 16 for further details on data collection, processing, and validation). The spatial distribution of the COI at the study site is shown in Figure 1.…”
Section: Human Mobility Datamentioning
confidence: 99%