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Optimizing future biodiversity sampling by citizen scientists.

Corey T Callaghan1,2,3, Alistair G B Poore2, Richard E Major1,3

  • 1Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales 2052, Australia.

Proceedings. Biological Sciences
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Summary
This summary is machine-generated.

Citizen science data can help track biodiversity during the sixth extinction. A new framework values each observation, guiding future sampling to maximize information for estimating population trends.

Keywords:
biodiversitycitizen sciencedynamic modelspredictive modellingspatial and temporal sampling

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Area of Science:

  • Ecology
  • Conservation Biology
  • Biodiversity Science

Background:

  • Earth is experiencing its sixth mass extinction event.
  • Biodiversity monitoring is crucial for conservation but faces funding limitations.
  • Citizen science data offers a scalable solution but is often noisy.

Purpose of the Study:

  • To maximize the information content of citizen science data for biodiversity trend estimation.
  • To develop a predictive framework for optimizing citizen science sampling strategies.

Main Methods:

  • Developed a novel framework to assign marginal value to citizen science sampling events.
  • Used this value to predict the importance of future observations for trend estimation.
  • Analyzed the spatial distribution of high-value sampling locations.

Main Results:

  • The framework successfully assigns value to citizen science observations for trend estimation.
  • Past observations are predictive of future high-value sampling locations.
  • Both frequently sampled 'hotspots' and sparsely sampled 'coldspots' offer valuable data.

Conclusions:

  • A balanced sampling strategy, incorporating both hotspots and coldspots, is optimal for biodiversity monitoring.
  • This approach enhances the utility of citizen science data for understanding population trends.
  • Effective use of citizen science data can improve conservation prioritization amidst funding constraints.