Evidence map›Paper›PMID 39221279›Full record

ArticlePeerJ2024

Reassessment of French breeding bird population sizes using citizen science and accounting for species detectability.

Jean Nabias, Luc Barbaro, Benoît Fontaine, Jérémy Dupuy, Laurent Couzi, Clément Vallé, Romain Lorrilliere

Abstract read
In one paragraph

Article in PeerJ, 2024. 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. Providing regular and frequent maps of losses and gains of farmland birds based on European monitoring data.Conservation biology : the journal of the Society for Conservation Biology · 2026
    Article
  2. 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

7 authors.

Jean NabiasMuséum National d'Histoire Naturelle, Centre d'Ecologie et des Sciences de la Conservation, Paris, France.
Luc BarbaroMuséum National d'Histoire Naturelle, Centre d'Ecologie et des Sciences de la Conservation, Paris, France.ORCID 0000-0001-7454-5765
Benoît FontaineMuséum National d'Histoire Naturelle, Centre d'Ecologie et des Sciences de la Conservation, Paris, France.
Jérémy DupuyLigue Pour la Protection des Oiseaux, Rochefort, France.
Laurent CouziLigue Pour la Protection des Oiseaux, Rochefort, France.
Clément ValléMuséum National d'Histoire Naturelle, Centre d'Ecologie et des Sciences de la Conservation, Paris, France.ORCID 0000-0003-3814-7975
Romain LorrilliereMuséum National d'Histoire Naturelle, Centre d'Ecologie et des Sciences de la Conservation, Paris, France.ORCID 0000-0003-1870-0278

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Higher efficiency in large-scale and long-term biodiversity monitoring can be obtained through the use of Essential Biodiversity Variables, among which species population sizes provide key data for conservation programs. Relevant estimations and assessment of actual population sizes are critical for species conservation, especially in the current context of global biodiversity erosion. However, knowledge on population size varies greatly, depending on species conservation status and ranges. While the most threatened or restricted-range species generally benefit from exhaustive counts and surveys, monitoring common and widespread species population size tends to be neglected or is simply more challenging to achieve. In such a context, citizen science (CS) is a powerful tool for the long-term monitoring of common species through the engagement of various volunteers, permitting data acquisition on the long term and over large spatial scales. Despite this substantially increased sampling effort, detectability issues imply that even common species may remain unnoticed at suitable sites. The use of structured CS schemes, including repeated visits, enables to model the detection process, permitting reliable inferences of population size estimates. Here, we relied on a large French structured CS scheme (EPOC-ODF) comprising 27,156 complete checklists over 3,873 sites collected during the 2021-2023 breeding seasons to estimate the population size of 63 common bird species using hierarchical distance sampling (HDS). These population size estimates were compared to the previous expert-based French breeding bird atlas estimations, which did not account for detectability issues. We found that population size estimates from the former French breeding bird atlas were lower than those estimated using HDS for 65% of species. Such a prevalence of lower estimations is likely due to more conservative estimates inferred from semi-quantitative expert-based assessments used for the previous atlas. We also found that species with long-range songs such as the Common Cuckoo (

Indexed as

BiodiversityBirdsCitizen ScienceConservation of Natural ResourcesPopulation DensityAnimalsFranceBiogeographyBird atlasesBreeding bird surveysCitizen scienceDetectabilityHierarchical distance sampling

Identifiers

PMID39221279
PMCPMC11363910

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.