Publications by authors named "Nirwan Sharma"

Widespread concern over declines in pollinating insects has led to numerous recommendations of which "pollinator-friendly" plants to grow and help turn urban environments into valuable habitat for such important wildlife. Whilst communicated widely by organisations and readily taken up by gardeners, the provenance, accuracy, specificity and timeliness of such recommendations remain unclear. Here we use data (6429 records) gathered through a UK-wide citizen science programme (BeeWatch) to determine food plant use by the nations' bumblebee species, and show that much of the plant use recorded does not reflect practitioner recommendations: correlation between the practitioners' bumblebee-friendly plant list (376 plants compiled from 14 different sources) and BeeWatch records (334 plants) was low (r = 0.

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Against a backdrop of accelerating digital innovation in nature conservation and environmental management, a real-world experiment was conducted with the research aims of assessing: 1) the effects of introducing a digital data-entry platform on volunteer data submission; and 2) the extent to which coordinators influence digital platform use by their volunteers. We focussed on a large-scale volunteer-based initiative aimed at eradicating the non-native American mink (Neovison vison) from northern Scotland. This geographically dispersed conservation initiative adopted a digital platform that allowed volunteers to submit records to a central database.

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In recent years, the number and scale of environmental citizen science programmes that involve lay people in scientific research have increased rapidly. Many of these initiatives are concerned with the recording and identification of species, processes which are increasingly mediated through digital interfaces. Here, we address the growing need to understand the particular role of digital identification tools, both in generating scientific data and in supporting learning by lay people engaged in citizen science activities pertaining to biological recording communities.

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The rapid rise of citizen science, with lay people forming often extensive biodiversity sensor networks, is seen as a solution to the mismatch between data demand and supply while simultaneously engaging citizens with environmental topics. However, citizen science recording schemes require careful consideration of how to motivate, train, and retain volunteers. We evaluated a novel computing science framework that allowed for the automated generation of feedback to citizen scientists using natural language generation (NLG) technology.

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To assess the ability of traditional biological recording schemes and lay citizen science approaches to gather data on species distributions and changes therein, we examined bumblebee records from the UK's national repository (National Biodiversity Network) and from BeeWatch. The two recording approaches revealed similar relative abundances of bumblebee species but different geographical distributions. For the widespread common carder (Bombus pascuorum), traditional recording scheme data were patchy, both spatially and temporally, reflecting active record centre rather than species distribution.

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