Polar Bear Numbers, Margins Of Error, & Consequences For Conservation Status

Large margins of error in polar bear population estimates means the conservation status threshold of a 30% decline (real or predicted) used by the US Endangered Species Act and the IUCN Red List is probably not valid for this species.

Polar_Bear_Biologist_USFWS_working_with_a_Bear_Oct 24 2001 Amstrup photo

Several recent subpopulation estimates have shown an increase between one estimate and another of greater than 30% yet deemed not to be statistacally significant due to large margins of error. How can such estimates be used to assess whether population numbers have declined enough to warrant IUCN Red List or ESA protection?

What do polar bear population numbers mean for conservation status, if anything?

Virtually all recent population size estimates for polar bear subpopulations have such enormous margins of error (aka confidence intervals) that even a 42% increase in one population count (details below) wasn’t enough to be statistically significant (Aars et al. 2017). That means the ESA and Red List definitions of ‘threatened’ with or ‘vulnerable’ to extinction  — based on the likelihood of a population decline of 30% or more over the next three generations — are using a criterion that’s not statistically valid for polar bears.

I discussed this issue of wide margins of error in subpopulation counts a few years ago (in relation to Eastern Beaufort bears and the effects of thick spring ice on population numbers, especially for 2006) but the problem has become more widespread and the implications more problematic, as discussed in my recent State of the Polar Bear Report 2017 (Crockford 2018).

Ultimately, large margins of error for subpopulation estimates threaten to undermine conservation status assessment — or at least they should.

In addition, some consensus polar bear specialists are selectively choosing to ignore statistical signficance and methological differences in population estimates to suit their own agenda, and by doing so, are giving the public misinformation. Two examples highlight the problems that large margins of error present: the last two Svalbard population survey estimates and the Western Hudson Bay population survey estimates since 1987 (made more complicated by methodological differences).

Full post

via The Global Warming Policy Forum (GWPF)

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May 2, 2018 at 12:07PM

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