Citizen Science in Schools: Students Collect Valuable Mammal Data for Science, Conservation, and Community Engagement

Schuttler, Stephanie G.; Sears, Rebecca; Orendain, Isabel; Khot, Rahul; Rubenstein, Daniel I.; Rubenstein, Nancy; Dunn, Robert R.; Baird, Elizabeth; Kandros, Kimberly; O’Brien, Timothy G.; Kays, Roland

doi:10.1093/biosci/biy141

Cited by 59 publications

(68 citation statements)

References 49 publications

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“…Previous studies of other organisms have found that research using data from citizen scientists produced results that were comparable F I G U R E 2 Land cover with small ape observations reported in social media or submitted directly by citizen scientists. Most sightings were inside forested areas near to roads for all three species of small apes with researcher-generated data (Aceves-Bueno et al, 2017;Horns et al, 2018aHorns et al, , 2018bSchuttler et al, 2019 Our results indicate that visitors to Malaysian forests notice small apes and that at least some of them value these encounters enough to post them on social media when they occur. Encouragingly, we found reliable reports of small ape sightings by citizen scientists in almost all states in Peninsular Malaysia, and the reports spanned most of the reported geographic distribution for each small ape taxon.…”

Section: Comparison and Critiquementioning

confidence: 64%

“…Previous studies of other organisms have found that research using data from citizen scientists produced results that were comparable with researcher‐generated data (Aceves‐Bueno et al, 2017; Horns et al, 2018a, 2018b; Schuttler et al, 2019). Small apes typically travel in the middle or upper forest canopy, and most small apes in Malaysia have a dark pelage, making them quite difficult to photograph.…”

Section: Comparison and Critiquementioning

confidence: 74%

“…For example, Wang et al (2018) used a combination of museum and online citizen science data to build reliable distribution maps for northern black widow spiders ( Latrodectus variolus ) and black purse‐web spiders ( Sphodros niger ). Similarly, Schuttler et al (2019) used camera trap data collected by children as young as 9 years old to obtain reliable mammal species occurrence data near schools in four countries. Horns et al (2018a) determined that estimates of population trends derived from eBird (an online repository for bird count data contributed by amateur birders) records differed little from those based on formal surveys, particularly for widespread species (but see Fogarty, Wohlfeil, & Fleishman, 2018; Horns, Adler, & Şekercioğlu, 2018b).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Are social media reports useful for assessing small ape occurrence? A pilot study from Peninsular Malaysia

Rameli

Lappan

Bartlett

et al. 2020

American J Primatol

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Citizen science‐based research has been used effectively to estimate animal abundance and breeding patterns, to monitor animal movement, and for biodiversity conservation and education. Here, we evaluate the feasibility of using social media observations to assess the distribution of small apes in Peninsular Malaysia. We searched for reports of small ape observations in Peninsular Malaysia on social media (e.g., blogs, Facebook, Instagram, Twitter, YouTube, iNaturalist, etc.), and also used online, radio, print messaging, and word of mouth to invite citizen scientists such as birders, amateur naturalists, hikers, and other members of the public to provide information about small ape observations made during their activities. These reports provided new information about the occurrence of all three species of small apes (Hylobates agilis, Hylobates lar, and Symphalangus syndactylus) in Peninsular Malaysia. Social media users reported observations of small apes in almost every state. Despite the fact that small apes are believed to occur primarily in the interior of large forested areas, most observations were from fairly small (<100 km2) forests near areas of high traffic and high human population (roads and urban areas). This suggests that most outdoor enthusiasts primarily visit well‐traveled and easily accessible areas, which results in biased sampling if only incidental observations reported on social media are used. A more targeted approach specifically soliciting reports from citizen scientists visiting large, less‐accessible forests may result in better sampling in these habitats. Social media reports indicated the presence of small apes in at least six habitats where they had not been previously reported. We verified the reported data based on whether reports included a date, location, and uploaded photographs, videos and/or audio recordings. Well‐publicized citizen science programs may also build awareness and enthusiasm about the conservation of vulnerable wildlife species.

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Section: Comparison and Critiquementioning

confidence: 64%

Section: Comparison and Critiquementioning

confidence: 74%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Are social media reports useful for assessing small ape occurrence? A pilot study from Peninsular Malaysia

Rameli

Lappan

Bartlett

et al. 2020

American J Primatol

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“…Children often have knowledge of non-native, charismatic species regularly seen in the media, such as lions, tigers or pandas, but have poor understanding of local species [36,37]. Introducing nature-based citizen science into schools could help to engage young people from a diverse range of backgrounds, reversing the 'extinction of experience' trend and increasing connection to nature [23,38], while helping them to engage with their studies and contributing to their learning [38,39].…”

Section: Citizen Sciencementioning

confidence: 99%

“…This creates targeted data collection for answering specific research questions, enabling participation by those available and able to follow that project design at the time (i.e., participants must be able to visit a specific study area during a particular time period). eMammal also supports camera trapping in schools, providing resources for teachers and encouraging pupils to design their own research questions and collect data using camera traps, which is then validated by experts on eMammal [39].…”

Section: Approaches Used In Camera Trapping and Citizen Sciencementioning

confidence: 99%

Innovations in Camera Trapping Technology and Approaches: The Integration of Citizen Science and Artificial Intelligence

Green

Rees

Stephens

et al. 2020

Animals

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Simple Summary: Camera traps, also known as "game cameras" or "trail cameras", have increasingly been used in wildlife research over the last 20 years. Although early units were bulky and the set-up was complicated, modern camera traps are compact, integrated units able to collect vast digital datasets. Some of the challenges now facing researchers include the time required to view, classify, and sort all of the footage collected, as well as the logistics of establishing and maintaining camera trap sampling arrays across wide geographic areas. One solution to this problem is to enlist or recruit the public for help as 'citizen scientists' collecting and processing data. Artificial Intelligence (AI) is also being used to identify animals in digital photos and video; however, this process is relatively new, and machine-based classifications are not yet fully reliable. By combining citizen science with AI, it should be possible to improve efficiency and increase classification accuracy, while simultaneously maintaining and promoting the benefits associated with public engagement with, and awareness of, wildlife.Abstract: Camera trapping has become an increasingly reliable and mainstream tool for surveying a diversity of wildlife species. Concurrent with this has been an increasing effort to involve the wider public in the research process, in an approach known as 'citizen science'. To date, millions of people have contributed to research across a wide variety of disciplines as a result. Although their value for public engagement was recognised early on, camera traps were initially ill-suited for citizen science. As camera trap technology has evolved, cameras have become more user-friendly and the enormous quantities of data they now collect has led researchers to seek assistance in classifying footage. This has now made camera trap research a prime candidate for citizen science, as reflected by the large number of camera trap projects now integrating public participation. Researchers are also turning to Artificial Intelligence (AI) to assist with classification of footage. Although this rapidly-advancing field is already proving a useful tool, accuracy is variable and AI does not provide the social and engagement benefits associated with citizen science approaches. We propose, as a solution, more efforts to combine citizen science with AI to improve classification accuracy and efficiency while maintaining public involvement.

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Large‐scale mammal monitoring: The potential of a citizen science camera‐trapping project in the United Kingdom

Hsing

Hill

Smith

et al. 2022

Ecol Sol and Evidence

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1. In light of global biodiversity loss, there is an increasing need for large-scale wildlife monitoring. This is difficult for mammals, since they can be elusive and nocturnal. In the United Kingdom, there is a lack of systematic, widespread mammal monitoring, and a recognized deficiency of data. Innovative new approaches are required.2. We developed MammalWeb, a portal to enable UK-wide camera trapping by a network of citizen scientists and partner organizations. MammalWeb citizen scientists contribute to both the collection and classification of camera trap data.Following trials in 2013-2017, MammalWeb has grown organically to increase its geographic reach (e.g. ∼2000 sites in Britain). It has so far provided the equivalent of over 340 camera trap-years of wild mammal monitoring, and produced nearly 440,000 classified image sequences and videos, of which, over 180,000 are mammal detections.3. We describe MammalWeb, its background, its development and the novel approaches we have for participation. We consider the data collected by Mammal-Web participants, especially in light of their relevance to the main goals of wildlife monitoring: to provide spatial data, abundance data and temporal behavioural data. MammalWeb can complement existing approaches to mammal monitoring. Explicit accounting for spatial and temporal patterns in animal activity enables accountingThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Citizen Science in Schools: Students Collect Valuable Mammal Data for Science, Conservation, and Community Engagement

Cited by 59 publications

References 49 publications

Are social media reports useful for assessing small ape occurrence? A pilot study from Peninsular Malaysia

Are social media reports useful for assessing small ape occurrence? A pilot study from Peninsular Malaysia

Innovations in Camera Trapping Technology and Approaches: The Integration of Citizen Science and Artificial Intelligence

Large‐scale mammal monitoring: The potential of a citizen science camera‐trapping project in the United Kingdom

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