The undetectability of global biodiversity trends using local species richness

• DOI: 10.1111/ecog.06604
• Publication Date: 2023-02-10T06:29:27Z
• Authors: Jose W. Valdez; Corey T. Callaghan; Jessica Junker; Andy Purvis; Samantha L. L. Hill; Henrique M. Pereira
• Keywords: Proxy (statistics); Global Change; Global biodiversity

Although species are being lost at alarming rates, previous research has provided conflicting results on the extent and even direction of global biodiversity change local scale. Here, we assessed ability to detect trends using richness how it is affected by number monitoring sites, sampling interval (i.e. time between original survey re‐survey site), measurement error (error richness), spatial grain (a proxy for taxa mobility) biases site‐selection biases). We use PREDICTS model‐based estimates as a real‐world distribution randomly selected sites calculate trends. found that while network with hundreds could in within 30‐year period, detecting doubled decade, increased 10‐fold three years yearly were undetectable. Measurement errors had non‐linear effect statistical power, 1% reducing power slight margin 5% drastically reliably any trend. The was also related grain, making harder sampled smaller plot sizes. Spatial not only reduced negative but sometimes yielded positive conclude accurate may simply be unfeasible current approaches. suggest representative implemented national level, combined models accounting biases, can help improve our understanding change.