Evidence map›Paper›PMID 33104962›Full record

ArticleEcotoxicology (London, England)2021

Investigating potential toxic effects of pollutants on population growth rates and probability of extinction for a representative squamate.

Scott M Weir, Christopher J Salice

Abstract read
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In one paragraph

Article in Ecotoxicology (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Toxic Effects on Thyroid Gland of Male Adult Lizards (International journal of molecular sciences · 2022
    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.

Scott M WeirDepartment of Biology, Queens University of Charlotte, Charlotte, NC, 28274, USA. weirs@queens.edu.
Christopher J SaliceEnvironmental Science and Studies & Department of Biological Sciences, Towson University, Towson, MD, 21252, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chemical contamination has been suggested as an important contributing factor to reptile population declines, but direct links are rarely reported. Population modeling provides a quantitative method to understand the long-term effects of contaminants on population persistence. We created a matrix model for Sceloporus lizards and investigated hypothetical toxic effects by reducing survival and reproductive parameters by 0 to 100% in 10% increments. We report effects on population growth rate (λ) and elasticity values for each stage due to these reductions. We then incorporated stochasticity to the model to simulate the variation seen in demographic data and quantified extinction risk. The deterministic model yielded a λ of 1.07 suggesting stability in some wild Sceloporus populations. A yearly reduction of 20 to 30% in demographic parameters was needed to push λ to decline in both our deterministic and stochastic simulations. Surprisingly, our baseline stochastic simulations had a 30% extinction probability despite a stable deterministic model. We tested three adjustments to the stochastic model, (1) increased survival/fecundity parameters, (2) higher starting densities, and (3) a density-dependent juvenile survival function. The model with density-dependent juvenile growth had the lowest extinction risk. Ultimately, 20 or 30% mortality every year is likely unrealistic, but our results provide insight in linking toxicity to population effects. Ultimately, very little reduction in demographics is needed to cause declines in these populations. Our generalized models provide important tools for screening-level risk assessment of chemical contamination, especially for taxonomic groups that tend to receive less research interest.

Indexed as

Environmental PollutantsPopulation GrowthAnimalsModels, BiologicalPopulation DynamicsProbabilityStochastic ProcessesEnvironmental PollutantsEcotoxicologyLizardPopulation modelingRisk assessment

Identifiers

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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.