Evidence map›Paper›PMID 40341191›Full record

ArticleScientific data2025

A dataset of pre-pandemic African protected area visitation.

Falko Buschke, Claudia Capitani, Philipp Schägner, Christophe Nsengiyumva, Hellen Okelo, Oumar Cissé, Susan Snyman

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. 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. 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.

Falko BuschkeEuropean Commission, Joint Research Centre, Ispra, Italy. falko.buschke@gmail.com.ORCID http://orcid.org/0000-0003-1167-7810
Claudia CapitaniEuropean Commission, Joint Research Centre, Ispra, Italy. claudia.capitani@ec.europa.eu.ORCID http://orcid.org/0000-0002-1899-8679
Philipp SchägnerEuropean Commission, Joint Research Centre, Ispra, Italy.
Christophe NsengiyumvaAfrican Leadership University, School of Wildlife Conservation, Kigali, Rwanda.
Hellen OkeloAfrican Leadership University, School of Wildlife Conservation, Kigali, Rwanda.
Oumar CisséAfrican Leadership University, School of Wildlife Conservation, Kigali, Rwanda.
Susan SnymanAfrican Leadership University, School of Wildlife Conservation, Kigali, Rwanda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When people visit protected areas, their presence can amplify public support for conservation and their spending closes conservation finance gaps and feeds local economies. Across Africa, protected areas are often presented as engines for poverty alleviation and rural development. Yet visitation data remains scarce for most of the continent. Here we present a dataset of African protected area visitation obtained from government sources as well as peer-reviewed and grey literature. The spatially explicit dataset includes 4,216 records from 341 protected areas in 34 countries. The earliest visitor counts date back to 1965, but the majority (78%) stem from between the years 2000 and 2020. While 22% of protected areas only have visitation data for a single year, the median protected area has six years of visitation data, facilitating temporal analyses. Moreover, the dataset is compatible with the World Database of Protected Areas, making it possible to compare visitation across governance types and management categories. Ultimately, the dataset provides baselines for post-pandemic nature tourism recovery and enables analyses of the factors determining protected area visitation.

Indexed as

Conservation of Natural ResourcesTourismAfricaHumansPandemics

Identifiers

PMID40341191
PMCPMC12062372

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.