Evidence map›Paper›PMID 36016822›Full record

ArticleEcology and evolution2022

rGAI: An R package for fitting the generalized abundance index to seasonal count data.

Emily B Dennis, Calliste Fagard-Jenkin, Byron J T Morgan

Open access · goldAbstract read
In one paragraph

Article in Ecology and evolution, 2022. 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
1.0field-weighted citation impact, top 18% of its field
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, 4 citations in OpenAlex.

  1. 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

3 authors at 3 institutions in 1 country.

Emily B DennisButterfly Conservation Dorset UK.ORCID https://orcid.org/0000-0003-2692-4415
Calliste Fagard-JenkinCentre for Research into Ecological and Environmental Modelling University of St Andrews St Andrews UK.ORCID https://orcid.org/0000-0001-6786-4936
Byron J T MorganSchool of Mathematics, Statistics and Actuarial Science University of Kent Kent UK.ORCID https://orcid.org/0000-0002-5465-8006
Butterfly Conservation · GBUniversity of Kent · GBUniversity of St Andrews · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The generalized abundance index (GAI) provides a useful tool for estimating relative population sizes and trends of seasonal invertebrates from species' count data and offers potential for inferring which external factors may influence phenology and demography through parametric descriptions of seasonal variation. We provide an R package that extends previous software with the ability to include covariates when fitting parametric GAI models, where seasonal variation is described by either a mixture of Normal distributions or a stopover model which provides estimates of life span. The package also generalizes the models to allow any number of broods/generations in the target population within a defined season. The option to perform bootstrapping, either parametrically or nonparametrically, is also provided. The new package allows models to be far more flexible when describing seasonal variation, which may be dependent on site-specific environmental factors or consist of many broods/generations which may overlap, as demonstrated by two case studies. Our open-source software, available at https://github.com/calliste-fagard-jenkin/rGAI, makes these extensions widely and freely available, allowing the complexity of GAI models used by ecologists and applied statisticians to increase accordingly.

Indexed as

flight periodgeneralized abundance indexmultivoltinephenologyseasonal abundancestopover model

Identifiers

PMID36016822
PMCPMC9396180
OpenAlexW4292831659

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.