Estimating the spatial coverage of citizen science for monitoring threatened species

Lloyd, Thomas; Fuller, Richard A.; Oliver, Jessica L.; Tulloch, Ayesha I. T.; Barnes, Megan; Steven, Rochelle

doi:10.1016/j.gecco.2020.e01048

Cited by 22 publications

(15 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Citizen science has become an important method in ecological and biodiversity research (Dickinson et al ., 2010; Ellwood et al ., 2017; McKinley et al ., 2017) from short‐term 1‐day ‘bioblitzes’ (Parker et al ., 2018; Aristeidou et al ., 2021) to long‐term species monitoring programmes (Chandler et al ., 2017; Lloyd et al ., 2020). Citizen science has broadened research scope and capacity, but also strengthened the relationship between the public, the natural world and the scientific process (Schuttler et al ., 2018; Adler et al ., 2020).…”

Section: Introductionmentioning

confidence: 99%

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

Perry

Sumner

Thompson³

et al. 2021

Insect Conserv Diversity

View full text Add to dashboard Cite

1. Citizen science is widely used in ecological research. Data verification of citizen collected data continues to be an issue, and confirming accurate species identification reported by citizens can be especially difficult.2. Here, we determine the efficacy of using remote learning to identify UK social wasp (Vespinae) species. Citizen scientists (N = 559) collected wasps and identified specimens to species level using a series of online videos and support material.3. A pre-and post-identification questionnaire, and a post-identification assessment test, obtained both qualitative and quantitative data for engagement and changes in identification skills. Some (13.5%) of the participants sent their samples in for expert verification of species identification. 4. Self-assessed skill ratings increased from 2.2/5 pre-identification to 3.5/5 postidentification process. Identification accuracy was high, with 85.6% of assessment test images and 96% of the verified specimens being identified correctly. In previous years, face-to-face public ID workshops with expert trainers yielded an identification accuracy of 91.3%. Eighty-seven percent of participants reported enjoying the experience and would take part again.5. Remote learning of identification skills in non-specialists can produce greater identification accuracy than face-to-face expert-led workshops, with lower resource requirements and enhanced engagement.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Perry

Sumner

Thompson³

et al. 2021

Insect Conserv Diversity

View full text Add to dashboard Cite

show abstract

“…Generally, the outcomes of citizen science projects show a strict correlation between human population density and data distribution (Johnston et al, 2020, Lloyd et al, 2020. In our case, it is almost impossible to find global data on the distribution of scubadivers, which activity is likely variable during the year and who are not strictly limited to their area of residence.…”

Section: Resultsmentioning

confidence: 73%

People’s contribution to the knowledge of Pycnogonida: citizen science in the case of a “problematic” taxon.

Colasanto¹,

Galli²

2021

View full text Add to dashboard Cite

Pycnogonida is a poorly known class of marine arthropods represented by nearly 1350 species described worldwide. We examined data about these organisms available on seven websites for photographs and information sharing among recreational naturalists. We found 384 observations, mainly with data about locality and date. Photos about 65 of them resulted correctly identified to the species level with certainty. The others refer to species whose identification requires a more in-depth analysis under a microscope. Unfortunately, this problem is common to a high percentage of pycnogonids. Therefore it seems unlikely that citizen scientists could contribute significantly to their knowledge. Nevertheless, for some species this would be possible and data on the presence of the taxon could be useful for more general studies at community level.

show abstract

“…Finally, community science data in general have been critiqued for being biased toward areas with higher human activity (Chandler et al, 2017; Lloyd et al, 2020; Theobald et al, 2015). Nevertheless, when analyses account for species and spatial bias, community science is a valuable tool for conservation (McKinley et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Clustering community science data to infer songbird migratory connectivity in the Western Hemisphere

et al. 2022

View full text Add to dashboard Cite

Migratory connectivity describes the spatial linkage among migrating individuals through time. Accounting for it is necessary for full annual cycle conservation planning, to avoid uneven protection leading to overall population declines. However, conventional methods used to study migratory connectivity usually demand substantial fiscal and human resources. We present a methodology that infers patterns of migratory connectivity for songbirds using relative abundance models created from eBird, a global community science program. We compare our inferences with previously described patterns of migratory connectivity for two species assumed to exhibit broadscale parallel migration strategies: wood thrush (Hylocichla mustelina) and Wilson's warbler (Cardellina pusilla). Initial findings suggest that our method has the potential to be a rapid and inexpensive way to infer broad patterns of connectivity for species that do not engage in leapfrog migration nor deviate much from parallel migration. Our flexible framework can be used to guide sampling designs for studies of migratory connectivity and to generate hypotheses for species in need of urgent conservation planning for which migratory connectivity has not yet been established.

show abstract

Estimating the spatial coverage of citizen science for monitoring threatened species

Cited by 22 publications

References 22 publications

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

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

People’s contribution to the knowledge of Pycnogonida: citizen science in the case of a “problematic” taxon.

Clustering community science data to infer songbird migratory connectivity in the Western Hemisphere

Contact Info

Product

Resources

About