Evidence map›Paper›PMID 38755428›Full record

ArticleAmbio2024

Participatory co-learning for human-wildlife coexistence: Reflections on a novel program applying systems thinking, nonviolent communication, and learning-based approaches.

Ruth Kansky, Tarek Maassarani, Joern Fischer

Abstract read
In one paragraph

Article in Ambio, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ruth KanskyDepartment of Conservation Ecology and Entomology, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa. ruthkansky@yahoo.com.ORCID http://orcid.org/0000-0002-4568-6566
Tarek MaassaraniJustice and Peace Studies, Georgetown University, Washington, DC, 20057, USA.
Joern FischerSocial-Ecological Systems Institute (SESI), Faculty of Sustainability, Leuphana Universitaet Lueneburg, Universitaetsallee 1, 21335, Lüneburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As wildlife habitats become increasingly fragmented, sharing landscapes with wildlife is becoming difficult and complex. Because stakeholders with diverging interests struggle to collaborate to manage human-wildlife interactions, new approaches are needed. Here we reflect on a novel participatory learning program we implemented with farmers in communal conservancies in the Zambezi region of Namibia. The 9 week program aimed to understand why human-wildlife conflict remained a challenge. We combined three theoretical framings in the program design-systems thinking, nonviolent communication, and learning based approaches. We summarize key outcomes of each session and reflect on the overall program. We found a synergistic effect of the three framings and concluded that our integrated program had been a useful collaborative learning tool to understand the human-wildlife governance system, identify interventions, empower communities, and build capacity for collaboration to improve human wellbeing and human-wildlife interactions. Drawing on our experience, we make suggestions for how the program could be adapted for similar or other environmental problems elsewhere.

Indexed as

Conservation of Natural ResourcesAnimalsAnimals, WildCommunicationEcosystemHumansLearningNamibiaSystems AnalysisCollaborative governanceHuman–wildlife conflict and coexistenceLearning-based approach in natural resource managementNonviolent communicationSystems thinkingWildlife governance

Identifiers

PMID38755428
PMCPMC11383895

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.