‘Citizen identification’: online learning supports highly accurate species identification for insect‐focussed citizen science

Perry, Jessica; Sumner, Seirian; Thompson, Cris; Hart, Adam G.

doi:10.1111/icad.12528

Cited by 7 publications

(7 citation statements)

References 42 publications

(42 reference statements)

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“…Of all investigated factors related to the individual respondent, training material resulted in the greatest decrease in misclassification rates. These results are similar to previous studies, which demonstrate that training material can improve quality of wildlife survey data (Ratnieks et al 2016;Katrak-Adefowora et al 2020;Perry et al 2021). Specifically, we saw the greatest reductions in error among adult males and fawns.…”

Section: Discussionsupporting

confidence: 90%

“…For example, practical training and educational materials are frequently provided to respondents of citizen science or volunteer-based projects with the intent of improving data reliability (Newman et al 2003;Cohn 2008;Steger et al 2017;Parsons et al 2018). Recent studies exploring the influence of longer-term (Danielsen et al 2014;van der Wal et al 2016) and single-session (Katrak-Adefowora et al 2020;Perry et al 2021) training programs on identifying wildlife images have generally found training to improve data reliability. However, the majority of previous research in this area has simply required respondents to classify wildlife images to the species level.…”

Section: Introductionmentioning

confidence: 99%

“…2016) and single-session (Katrak-Adefowora et al . 2020; Perry et al . 2021) training programs on identifying wildlife images have generally found training to improve data reliability.…”

Section: Introductionmentioning

confidence: 99%

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Training and experience increase classification accuracy in white-tailed deer camera surveys

et al. 2022

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Context Use of camera trap data in wildlife research is reliant on accurate classification of animals at the species, sex–age category or individual level. One such example is white-tailed deer (Odocoileus virginianus) camera surveys, which are often conducted to produce demographic estimates used by managers to establish harvest goals for a population. Previous research suggests that misclassification of deer by sex–age category (e.g. adult male, adult female, fawn) is common in these surveys, and represents a source of bias that could misinform important management decisions. Aim To examine whether training material has an effect on classification accuracy of white-tailed deer and explore other observer-based, experiential factors as they relate to classification accuracy. Methods We developed and tested the efficacy of species-specific training material designed to reduce sex–age misclassifications associated with white-tailed deer images. Key results Exposure to training material resulted in the greatest improvement in classification accuracy of deer images compared with any other respondent-based factors we investigated. Other factors, such as professional experience as a wildlife biologist, field experience viewing white-tailed deer and experience viewing deer images from camera traps, were positively associated with classification accuracy of deer images. Conclusions Our findings suggest that training material has the ability to reduce misclassifications, leading to more accurate demographic estimates for white-tailed deer populations. We also found that prior experience using camera traps and familiarity with target species was positively related to classification accuracy. Implications Species-specific training material would provide a valuable resource to wildlife managers tasked with classifying animals at the species, sex–age category or individual level.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

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Training and experience increase classification accuracy in white-tailed deer camera surveys

et al. 2022

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“…The advent of community science observation datasets has exponentially increased the availability of species occurrences for habitat suitability modelling (Bradter et al, 2018;Coxen et al, 2017;Jessica et al, 2014). Although the majority of such studies focus on vertebrate taxa, utilising community science data for insect SDMs is slowly gaining momentum (Perry et al, 2021). One of the more urgent endeavours of SDMs using community-science data is biodiversity conservation (Silva et al, 2013;Silva et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

Dynamic distribution modelling of the swamp tigertail dragonflySynthemis eustalacta(Odonata: Anisoptera: Synthemistidae) over a 20‐year bushfire regime

Goodman

Kass

Ware

2022

Ecological Entomology

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1. Intensity and severity of bushfires in Australia have increased over the past few decades due to climate change, threatening habitat loss for numerous species. Although the impact of bushfires on vertebrates is well-documented, the corresponding effects on insect taxa are rarely examined, although they are responsible for key ecosystem functions and services. Understanding the effects of bushfire seasons on insect distributions could elucidate long-term impacts and patterns of ecosystem recovery.2. Here, the authors investigated the effects of recent bushfires, land-cover change, and climatic variables on the distribution of a common and endemic dragonfly, the swamp tigertail (Synthemis eustalacta) (Burmeister, 1839), which inhabits forests that have recently undergone severe burning. The authors used a temporally dynamic species distribution modelling approach that incorporated 20 years of community-science data on dragonfly occurrence and predictors based on fire, land cover, and climate to make yearly predictions of suitability. The authors also compared this to an approach that combines multiple temporally static models that use annual data.3. The authors found that for both approaches, fire-specific variables had negligible importance for the models, while the percentage of tree and non-vegetative cover were most important. The authors also found that the dynamic model outperformed the static ones, based on cross-validation omission rate. Model predictions indicated temporal variation in area and spatial arrangement of suitable habitat, but no patterns of habitat expansion, contraction, or shifting. 4. These results highlight not only the efficacy of dynamic modelling to capture spatiotemporal variables such as vegetation cover for an endemic insect species, but also provide a novel approach to mapping species distributions with sparse locality records.

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“…Members of the UK's public were invited to hang a simple homemade bottle trap in their gardens for a week in late August and then post the samples to identification hubs where experts could verify species identity. Since 2020, participants have identified their own samples using online identification tools developed for the project (Perry et al, 2021). The project has proved highly successful in engaging with the public: between 2017 and 2021, 3389 unique participants/participant groups set out 7916 traps across the UK, catching over 62,000 wasps.…”

Section: Introductionmentioning

confidence: 99%

Using citizen science data to assess the population genetic structure of the common yellowjacket wasp, Vespula vulgaris

Cunningham‐Eurich,

Kontou,

Yordanova

et al. 2023

Insect Molecular Biology

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Monitoring insect genetic diversity and population structure has never been more important to manage the biodiversity crisis. Citizen science has become an increasingly popular tool to gather ecological data affordably across a wide range of spatial and temporal scales. To date, most insect‐related citizen science initiatives have focused on occurrence and abundance data. Here, we show that poorly preserved insect samples collected by citizen scientists can yield population genetic information, providing new insights into population connectivity, genetic diversity and dispersal behaviour of little‐studied insects. We analysed social wasps collected by participants of the Big Wasp Survey, a citizen science project that aims to map the diversity and distributions of vespine wasps in the UK. Although Vespula vulgaris is a notorious invasive species around the world, it remains poorly studied in its native range. We used these data to assess the population genetic structure of the common yellowjacket V. vulgaris at different spatial scales. We found a single, panmictic population across the UK with little evidence of population genetic structuring; the only possible limit to gene flow is the Irish sea, resulting in significant differentiation between the Northern Ireland and mainland UK populations. Our results suggest that queens disperse considerable distances from their natal nests to found new nests, resulting in high rates of gene flow and thus little differentiation across the landscape. Citizen science data has made it feasible to perform this study, and we hope that it will encourage future projects to adopt similar practices in insect population monitoring.

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‘Citizen identification’: online learning supports highly accurate species identification for insect‐focussed citizen science

Cited by 7 publications

References 42 publications

Training and experience increase classification accuracy in white-tailed deer camera surveys

Training and experience increase classification accuracy in white-tailed deer camera surveys

Dynamic distribution modelling of the swamp tigertail dragonflySynthemis eustalacta(Odonata: Anisoptera: Synthemistidae) over a 20‐year bushfire regime

Using citizen science data to assess the population genetic structure of the common yellowjacket wasp, Vespula vulgaris

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