Evidence map›Paper›PMID 36178009›Full record

ArticleEcological applications : a publication of the Ecological Society of America2022

Spatio-temporal changes in chimpanzee density and abundance in the Greater Mahale Ecosystem, Tanzania.

Joana S Carvalho, Fiona A Stewart, Tiago A Marques, Noemie Bonnin, Lilian Pintea, Adrienne Chitayat, Rebecca Ingram, Richard J Moore, Alex K Piel

Abstract read
In one paragraph

Article in Ecological applications : a publication of the Ecological Society of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Chimpanzees (Ecology and evolution · 2025
    Article
  4. Article
  5. Spatio-temporal changes in chimpanzee density and abundance in the Greater Mahale Ecosystem, Tanzania.Ecological applications : a publication of the Ecological Society of America · 2022
    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

9 authors.

Joana S CarvalhoSchool of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK.ORCID 0000-0002-4235-1242
Fiona A StewartSchool of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK.ORCID 0000-0002-4929-4711
Tiago A MarquesSchool of Mathematics and Statistics, University of St. Andrews, St. Andrews, UK.ORCID 0000-0002-2581-1972
Noemie BonninSchool of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK.ORCID 0000-0001-5529-7452
Lilian PinteaDepartment of Conservation Science, The Jane Goodall Institute, Washington, District of Columbia, USA.ORCID 0000-0001-7419-6411
Adrienne ChitayatInstitute of Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands.ORCID 0000-0003-2651-4010
Rebecca IngramGreater Mahale Ecosystem Research and Conservation Project, Dar es Salaam, Tanzania.
Richard J MooreSchool of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, UK.
Alex K PielGreater Mahale Ecosystem Research and Conservation Project, Dar es Salaam, Tanzania.ORCID 0000-0002-4674-537X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Species conservation and management require reliable information about animal distribution and population size. Better management actions within a species' range can be achieved by identifying the location and timing of population changes. In the Greater Mahale Ecosystem (GME), western Tanzania, deforestation due to the expansion of human settlements and agriculture, annual burning, and logging are known threats to wildlife. For one of the most charismatic species, the endangered eastern chimpanzee (Pan troglodytes schweinfurthii), approximately 75% of the individuals are distributed outside national park boundaries, requiring monitoring and protection efforts over a vast landscape of various protection statuses. These efforts are especially challenging when we lack data on trends in density and population size. To predict spatio-temporal chimpanzee density and abundance across the GME, we used density surface modeling, fitting a generalized additive model to a 10-year time-series data set of nest counts based on line-transect surveys. The chimpanzee population declined at an annual rate of 2.41%, including declines of 1.72% in riparian forests (from this point forward, forests), 2.05% in miombo woodlands (from this point forward, woodlands) and 3.45% in nonforests. These population declines were accompanied by ecosystem-wide declines in vegetation types of 1.36% and 0.32% per year for forests and woodlands, respectively; we estimated an annual increase of 1.35% for nonforests. Our model predicted the highest chimpanzee density in forests (0.86 chimpanzees/km

Indexed as

EcosystemPan troglodytesAnimalsConservation of Natural ResourcesForestsHumansTanzaniaconservationdensity surface modelingdetection function estimationeastern chimpanzeegeneralized additive modelsgreat apesline-transect distance samplingspatially explicit models

Identifiers

PMID36178009
PMCPMC10078593

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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.