Reconciling Biodiversity Indicators to Guide Understanding and Action

Many metrics can be used to capture trends in biodiversity and, in turn, these metrics inform biodiversity indicators. Sampling biases, genuine differences between metrics, or both, can often cause indicators to appear to be in conflict. This lack of congruence confuses policy makers and the general...

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Bibliographic Details
Published in:Conservation letters 2016-11, Vol.9 (6), p.405-412
Main Authors: Hill, Samantha L.L., Harfoot, Mike, Purvis, Andy, Purves, Drew W., Collen, Ben, Newbold, Tim, Burgess, Neil D., Mace, Georgina M.
Format: Article
Language:English
Subjects:
Aichi targets
Biodiversity
biodiversity metrics
biodiversity trends
Endangered & extinct species
Extinction
Global biodiversity indicators
Indicators
Madingley model
PREDICTS model
Simulation
Species richness
Trends
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Summary:Many metrics can be used to capture trends in biodiversity and, in turn, these metrics inform biodiversity indicators. Sampling biases, genuine differences between metrics, or both, can often cause indicators to appear to be in conflict. This lack of congruence confuses policy makers and the general public, hindering effective responses to the biodiversity crisis. We show how different and seemingly inconsistent metrics of biodiversity can, in fact, emerge from the same scenario of biodiversity change. We develop a simple, evidence‐based narrative of biodiversity change and implement it in a simulation model. The model demonstrates how, for example, species richness can remain stable in a given landscape, whereas other measures (e.g. compositional similarity) can be in sharp decline. We suggest that linking biodiversity metrics in a simple model will support more robust indicator development, enable stronger predictions of biodiversity change, and provide policy‐relevant advice at a range of scales.
ISSN:1755-263X
1755-263X
DOI:10.1111/conl.12291