Evidence map›Paper›PMID 40870570›Full record

ArticleInsects2025

Investigating the Spatial Biases and Temporal Trends in Insect Pollinator Occurrence Data on GBIF.

Ehsan Rahimi, Chuleui Jung

Abstract read
In one paragraph

Article in Insects, 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
  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

2 authors.

Ehsan RahimiAgricultural Research Institute, GyeongKuk National University, Andong 36729, Republic of Korea.ORCID 0000-0002-8401-472X
Chuleui JungAgricultural Research Institute, GyeongKuk National University, Andong 36729, Republic of Korea.

Funding

National Research Foundation of Korea 2022K1A3A9A05036394National Research Foundation of Korea NRF-2018R1A6A1A03024862rural development administration RS-2023-00232847
6 · The paper itself

Abstract

Research in biogeography, ecology, and biodiversity hinges on the availability of comprehensive datasets that detail species distributions and environmental conditions. At the forefront of this endeavor is the Global Biodiversity Information Facility (GBIF). This study focuses on investigating spatial biases and temporal trends in insect pollinator occurrence data within the GBIF dataset, specifically focusing on three pivotal pollinator groups: bees, hoverflies, and butterflies. Addressing these gaps in GBIF data is essential for comprehensive analyses and informed pollinator conservation efforts. We obtained occurrence data from GBIF for seven bee families, six butterfly families, and the Syrphidae family of hoverflies in 2024. Spatial biases were addressed by eliminating duplicate records with identical latitude and longitude coordinates. Species richness was assessed for each family and country. Temporal trends were examined by tallying annual occurrence records for each pollinator family, and the diversity of data sources within GBIF was evaluated by quantifying unique data publishers. We identified initial occurrence counts of 4,922,390 for bees, 1,703,131 for hoverflies, and 31,700,696 for butterflies, with a substantial portion containing duplicate records. On average, 81.4% of bee data, 77.2% of hoverfly data, and 65.4% of butterfly data were removed post-duplicate elimination for dataset refinement. Our dataset encompassed 9286 unique bee species, 2574 hoverfly species, and 17,895 butterfly species. Our temporal analysis revealed a notable trend in data recording, with 80% of bee and butterfly data collected after 2022, and a similar threshold for hoverflies reached after 2023. The United States, Germany, the United Kingdom, and Sweden consistently emerged as the top countries for occurrence data across all three groups. The analysis of data publishers highlighted iNaturalist.org as a top contributor to bee data. Overall, we uncovered significant biases in the occurrence data of pollinators from GBIF. These biases pose substantial challenges for future research on pollinator ecology and biodiversity conservation.

Indexed as

beesbutterfliesGBIFhoverfliespollinatorsspecies distribution models

Identifiers

PMID40870570
PMCPMC12386186

What Socratic 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 Socratic graph.