Evidence map›Paper›PMID 28031796›Full record

ArticleEcology and evolution2016

The effects of demographic stochasticity and parameter uncertainty on predicting the establishment of introduced species.

Gian Marco Palamara, Francesco Carrara, Matthew J Smith, Owen L Petchey

Abstract read
In one paragraph

Article in Ecology and evolution, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Success and failure of ecological management is highly variable in an experimental test.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  3. Article
  4. 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

4 authors.

Gian Marco PalamaraDepartment of Evolutionary Biology and Environmental Studies University of Zurich Zürich Switzerland; Computational Science Laboratory Microsoft Research Cambridge UK.
Francesco CarraraRalph, M. Parson Laboratory, Department of Civil and Environmental Engineering Massachusetts Institute of Technology Cambridge MA USA; Department of Civil, Environmental and Geomatic Engineering ETH Zürich Switzerland.
Matthew J SmithComputational Science Laboratory Microsoft Research Cambridge UK.
Owen L PetcheyDepartment of Evolutionary Biology and Environmental Studies University of Zurich Zürich Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasive species are a serious threat to biodiversity worldwide and predicting whether an introduced species will first establish and then become invasive can be useful to preserve ecosystem services. Establishment is influenced by multiple factors, such as the interactions between the introduced individuals and the resident community, and demographic and environmental stochasticity. Field observations are often incomplete or biased. This, together with an imperfect knowledge of the ecological traits of the introduced species, makes the prediction of establishment challenging. Methods that consider the combined effects of these factors on our ability to predict the establishment of an introduced species are currently lacking. We develop an inference framework to assess the combined effects of demographic stochasticity and parameter uncertainty on our ability to predict the probability of establishment following the introduction of a small number of individuals. We find that even moderate levels of demographic stochasticity influence both the probability of establishment, and, crucially, our ability to correctly predict that probability. We also find that estimation of the demographic parameters of an introduced species is fundamental to obtain precise estimates of the interaction parameters. For typical values of demographic stochasticity, the drop in our ability to predict an establishment can be 30% when having priors on the demographic parameters compared to having their accurate values. The results from our study illustrate how demographic stochasticity may bias the prediction of the probability of establishment. Our method can be applied to estimate probability of establishment of introduced species in field scenarios, where time series data and prior information on the demographic traits of the introduced species are available.

Indexed as

Bayesian inferencebirth and death processdemographic stochasticityestablishment probabilityinvasion dynamicsLotka–Volterra equations

Identifiers

PMID28031796
PMCPMC5167034

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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.