Evidence map›Paper›PMID 40175470›Full record

ArticleScientific reports2025

Use of cover data to model species abundance distributions through continuous probability functions.

Halime Moradi, Paulo Inácio Prado, Jens Oldeland, Paulo A V Borges, Simone Fattorini

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Halime MoradiCEN Center for Earth System Research and Sustainability, Institute of Geography, University of Hamburg, Bundesstrasse 55, 20146, Hamburg, Germany. halime.moradi@uni-hamburg.de.
Paulo Inácio PradoBiosciences Institute at São Paulo University, Rua do Matão, travessa 14, nº 321, São Paulo, 05508-900, SP, Brazil.
Jens OldelandInstitute for Globally Distributed Open Research and Education (IGDORE), Burgunderweg 9d, 22453, Hamburg, Germany.
Paulo A V BorgesUniversity of Azores, Centre for Ecology, Evolution and Environmental Changes (cE3c)/Azorean Biodiversity Group, CHANGE-Global Change and Sustainability Institute, Faculty of Agricultural Sciences and Environment, Rua Capitão João d´Avila, Pico da Urze, Angra do Heroísmo, 9700-042, Portugal.
Simone FattoriniDepartment of Life, Health and Environmental Sciences, University of L'Aquila, Via Vetoio, L'Aquila, 67100, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Species abundance distribution (SAD) models describe the abundances of the species within ecological communities. SAD modelling has been developed using frequency distributions that require the use of count data (number of individuals). However, many organisms, such as most plants, cannot be counted. Instead, abundance is estimated using cover values. We show here how SAD approaches conceived for modelling frequency distributions based on counts can be modified to deal with continuous distributions and provide an application using relative plant cover as a continuous measure of abundance. We applied several SAD models using continuous probability functions to investigate how plant SADs changed along a wide (2,500 m) elevational gradient in the Alborz Mountains (Iran). We found that most communities were adequately fitted by the Weibull distribution, whose parameters changed along the gradient in response to the interplay between biotic and environmental filtering processes. The use of continuous probability functions in SAD modelling should be encouraged in research dealing with plant communities and other organisms for which counting individuals is theoretically or practically impossible.

Indexed as

BiodiversityEcosystemModels, BiologicalPlantsModels, StatisticalProbabilityAlborz mountainsCommunity ecologyContinuous distributionsElevational gradientPlant species abundance distributionsWeibull model

Identifiers

PMID40175470
PMCPMC11965384

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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.