Evidence map›Paper›PMID 31679499›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019

How predictable is extinction? Forecasting species survival at million-year timescales.

Peter Smits, Seth Finnegan

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Towards an Analytical Biology.Current genomics · 2024
    Article
  5. Article
  6. How predictable are mass extinction events?Royal Society open science · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Insights from the past: unique opportunity or foreign country?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Peter SmitsDepartment of Integrative Biology, University of California Berkeley, Berkeley, CA, USA.
Seth FinneganDepartment of Integrative Biology, University of California Berkeley, Berkeley, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A tenet of conservation palaeobiology is that knowledge of past extinction patterns can help us to better predict future extinctions. Although the future is unobservable, we can test the strength of this proposition by asking how well models conditioned on past observations would have predicted subsequent extinction events at different points in the geological past. To answer this question, we analyse the well-sampled fossil record of Cenozoic planktonic microfossil taxa (Foramanifera, Radiolaria, diatoms and calcareous nanoplankton). We examine how extinction probability varies over time as a function of species age, time of observation, current geographical range, change in geographical range, climate state and change in climate state. Our models have a 70-80% probability of correctly forecasting the rank order of extinction risk for a random out-of-sample species pair, implying that determinants of extinction risk have varied only modestly through time. We find that models which include either historical covariates or account for variation in covariate effects over time yield equivalent forecasts, but a model including both is overfit and yields biased forecasts. An important caveat is that human impacts may substantially disrupt range-risk dynamics so that the future will be less predictable than it has been in the past. This article is part of a discussion meeting issue 'The past is a foreign country: how much can the fossil record actually inform conservation?'

Indexed as

BiodiversityClimate ChangeExtinction, BiologicalFossilsBiological EvolutionConservation of Natural ResourcesDiatomsForaminiferaForecastingPaleontologyPlanktonconservationextinctionforecastingpalaeobiology

Identifiers

PMID31679499
PMCPMC6863491

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.