Data_Sheet_1_Measuring the Efficiency of Alternative Biodiversity Monitoring Sampling Strategies.PDF (515.54 kB)
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Data_Sheet_1_Measuring the Efficiency of Alternative Biodiversity Monitoring Sampling Strategies.PDF

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posted on 2022-02-16, 04:24 authored by Gema Hernan, Alexandra K. Dubel, Jennifer E. Caselle, David J. Kushner, Robert J. Miller, D. C. Reed, Joshua L. Sprague, Andrew Rassweiler

Monitoring is a crucial tool for measuring the progress and success of environmental policies and management programs. While many studies have evaluated the effectiveness of biodiversity sampling methods, few have compared their efficiency, which is crucial given the funding constraints present in all conservation efforts. In this study we demonstrate how existing analytical tools can be applied to (i) assess the relationship between sampling effort and resulting confidence in biodiversity metrics, and (ii) compare the efficiency of different methods for monitoring biodiversity. We tested this methodology on data from marine fish surveys, including: roving surveys within permanent areas, randomly placed belt transects, and randomly placed transects conducted by citizen scientists using a reduced species list. We constructed efficiency curves describing how increasing effort spent on each method reduced uncertainty in biodiversity estimates and the associated ability to detect change in diversity. All programs produced comparable measurements of species diversity for all metrics despite substantial differences in the species being surveyed by each method. The uncertainty of diversity estimations fell faster and reached a lower level for the roving diver method. Strikingly, the transect method conducted by citizen scientists performed almost identically to the more taxonomically resolved transect method conducted by professional scientists, suggesting that sampling strategies that recorded only a subset of species could still be effective, as long as the excluded species were chosen strategically. The methodology described here can guide decisions about how to measure biodiversity and optimize the resources available for monitoring, ultimately improving management outcomes.