A method to value nature-related webcam viewing: the value of virtual use with application to brown bear webcam viewing

Loomis, John B.; Richardson, Leslie; Huber, Christopher; Skibins, Jeffrey C.; Sharp, Ryan L.

doi:10.1080/21606544.2018.1483842

Cited by 10 publications

(12 citation statements)

References 10 publications

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“…Evidence suggests online wildlife viewers spend large amounts of time watching bearcams, developing online communities, and recruiting friends and family (Skibins et al, 2022). Although these elements occur in traditional ecotourism experiences, their new online role coupled with a highly dedicated audience (Skibins andSharp, 2017, 2019;Loomis et al, 2018;Richardson and Lewis, 2022), committed to a single species, can broaden engagement opportunities.…”

Section: Discussionmentioning

confidence: 99%

“…Webcams can provide similar experiences to being onsite while simultaneously eliminating onsite based impacts of a tourist. Webcams have also been shown to be capable of generating desired conservation outcomes of awareness, pro-conservation behaviors, and emotional connectivity (Loomis et al, 2018;Skibins and Sharp, 2019). Given the associated outcomes, webcam viewing may also be considered a new form of pro-conservation behavior (Miller and Freimund, 2017b;Schuler and Skibins, 2022).…”

Section: Bear Tourismmentioning

confidence: 99%

“…Independent variables were adapted from literature surrounding onsite and online bear viewing (Verbos et al, 2015;Skibins andSharp, 2017, 2019;Loomis et al, 2018;Keating and Krannich, 2020). Experiential items consisted of close-ended items addressing frequency/duration of viewing experience, preferences for webcam locations, and previous experience of webcam viewing.…”

Section: Independent Variablesmentioning

confidence: 99%

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Is one the loneliest number? Impact of tourists' ability to identify individual bears on conservation outcomes

Skibins¹,

Richardson²,

Lewis³

et al. 2023

Front. Sustain. Tour.

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IntroductionA fundamental component of ecotourism is resource conservation. Oftentimes, that resource is wildlife. Within the wildlife-centric ecotourism experience, tourists' encounters are most often with individual animals, or a small subset of the population (i.e., not the species as a whole). However, most conservation efforts are focused at the species level. This article explores the relationship between tourists' ability to identify individual animals and conservation outcomes.MethodsData were obtained from 3,853 online surveys from viewers of the Katmai National Park and Preserve webcams (bearcams).ResultsThe majority of respondents (70%) indicated they could identify individual bears. Respondents who could identify individual bears had significantly higher scores for conservation outcomes (i.e., awareness, behavioral intention, and emotional connection). Furthermore, identifying an individual bear as a favorite yielded significantly higher scores for emotional connectivity and support for conservation programs.DiscussionThus, the ability to identify individual animals, when viewing wildlife, can improve conservation outcomes. Practitioners could consider incorporating strategies to improve tourists' identification skills as a method to cultivating conservation outcomes.

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Section: Discussionmentioning

confidence: 99%

Section: Bear Tourismmentioning

confidence: 99%

Section: Independent Variablesmentioning

confidence: 99%

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Is one the loneliest number? Impact of tourists' ability to identify individual bears on conservation outcomes

Skibins¹,

Richardson²,

Lewis³

et al. 2023

Front. Sustain. Tour.

Self Cite

View full text Add to dashboard Cite

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“…Other wildlife interpretation initiatives include attractive technologies for remote viewing of wildlife, such as use of webcams or drones to broadcast images of wildlife behaviour from nesting or breeding sites (e.g. Chambers, 2007; Loomis, Richardson, Huber, Skibins, & Sharp, 2018; Skibins & Sharp, 2018). Several studies have found that involvement of lay‐people in scientific projects helps to raise their feelings of responsibility towards the environment and foster positive conservation attitudes and behaviours (Ballard, Dixon, & Harris, 2017; Evans et al., 2005; Newman, Buesching, & Macdonald, 2003; Toomey & Domroese, 2013).…”

Section: Embarking On a New Chapter Of Conservation Messagingmentioning

confidence: 99%

Principles for including conservation messaging in wildlife‐based tourism

et al. 2020

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There is growing evidence that wildlife‐based tourism can be a valuable pathway to transform the environmental knowledge, attitudes and behaviours of tourists, if complemented by effective conservation messaging and proactive interpretive experiences. Yet, such conservation messaging is not always a priority for many wildlife‐based tourism operators, who often avoid exposing happy tourists to the daunting biodiversity crisis. In this paper, we argue that failing to encourage tourists to do more on behalf of wildlife represents a missed opportunity for conservation. Based on a comprehensive review of the academic literature, we show that conservation messaging is virtually absent from many mainstream wildlife‐based tourism operations, often failing to connect global audiences to conservation issues. We found that the scholarly literature on the effectiveness of different techniques, approaches and contents of conservation messaging in wildlife‐based tourism is meagre at best. Yet, alternative forms of communicating conservation‐related messages are opening new avenues to broaden the conservation potential of wildlife‐based tourism. We suggest a set of principles for improving the implementation of conservation messaging in wildlife‐based tourism operations in order to maximize their educational potential. We end by calling for further research efforts on the factors implicated in effective conservation messaging in wildlife‐based tours in order to pave the way for a new era of conservation‐oriented tourism.

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“…Thousands of outdoor webcams are installed around the globe, providing big sensor data (Jacobs et al 2009). There is a multitude of fields in which images from networks of webcams at fixed locations are exploited, such as hydrology (Giuliani et al 2016;Fedorov 2017;Tom et al 2020), the observation of animals (Loomis et al 2018) and phenological properties (Bórnez et al 2020;Bater et al 2011), or the monitoring of pedestrian activity and density (Petrasova et al 2019;Hipp et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Convective-Scale Assimilation of Cloud Cover from Photographs Using a Machine Learning Forward Operator

Reinhardt

Schoger

Kurzrock³

et al. 2023

Artificial Intelligence for the Earth Systems

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This paper presents an innovational way of assimilating observations of clouds into the ICOsahedral Nonhydrostatic weather forecasting model for regional scale, ICON-D2, which is operated by Deutscher Wetterdienst (DWD). A convolutional neural network (CNN) is trained to detect clouds in camera photographs. The network’s output is a greyscale picture, in which each pixel has a value between 0 and 1, describing the probability of the pixel belonging to a cloud (1) or not (0). By averaging over a certain box of the picture a value for the cloud cover of that region is obtained. A forward operator is built to map an ICON model state into the observation space. A three dimensional grid in the space of the camera’s perspective is constructed and the ICON model variable cloud cover (CLC) is interpolated onto that grid. The maximum CLC along the rays that fabricate the camera grid, is taken as a model equivalent for each pixel. After superobbing, monitoring experiments have been conducted to compare the observations and model equivalents over a longer time period, yielding promising results. Further we show the performance of a single assimilation step as well as a longer assimilation experiment over a time period of six days which also yields good results. These findings are a proof of concept and further research has to be invested before these new innovational observations can be assimilated operationally in any numerical weather prediction (NWP) model.

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A method to value nature-related webcam viewing: the value of virtual use with application to brown bear webcam viewing

Cited by 10 publications

References 10 publications

Is one the loneliest number? Impact of tourists' ability to identify individual bears on conservation outcomes

Is one the loneliest number? Impact of tourists' ability to identify individual bears on conservation outcomes

Principles for including conservation messaging in wildlife‐based tourism

Convective-Scale Assimilation of Cloud Cover from Photographs Using a Machine Learning Forward Operator

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