Evidence map›Paper›PMID 28382488›Full record

ArticleEnvironmental management2017

Micro-Credit and Community Wildlife Management: Complementary Strategies to Improve Conservation Outcomes in Serengeti National Park, Tanzania.

Emmanuel Kaaya, Margaret Chapman

Abstract read
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In one paragraph

Article in Environmental management, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Emmanuel KaayaRubondo Island National Park, P.O. Box 111, Geita, Tanzania.
Margaret ChapmanSchool of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD, Australia. m.d.chapman@uq.edu.au.ORCID 0000-0002-8215-7081

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Community wildlife management programs in African protected areas aim to deliver livelihood and social benefits to local communities in order to bolster support for their conservation objectives. Most of these benefits are delivered at the community level. However, many local people are also seeking more individual or household-level livelihood benefits from community wildlife management programs because it is at this level that many of the costs of protected area conservation are borne. Because community wildlife management delivers few benefits at this level, support for their conservation objectives amongst local people often declines. The study investigated the implications of this for reducing poaching in Serengeti National Park, Tanzania. Three community wildlife management initiatives undertaken by Park management were compared with regard to their capacity to deliver the individual and household-level benefits sought by local people: community conservation services, wildlife management areas and community conservation banks. Interviews were carried out with poachers and local people from four villages in the Western Serengeti including members of village conservation banks, as well as a number of key informants. The results suggest that community conservation banks could, as a complementary strategy to existing community wildlife management programs, potentially provide a more effective means of reducing poaching in African protected areas than community wildlife management programs alone.

Indexed as

Animals, WildParks, RecreationalAnimalsCommunity ParticipationConservation of Natural ResourcesHumansProgram DevelopmentTanzaniaCommunity wildlife managementHouseholdsLivelihoodsMicro-creditParticipationTanzania

Identifiers

What OpenQuestion holds

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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.