Evidence map›Paper›PMID 33564057›Full record

ArticleScientific reports2021

Big trees drive forest structure patterns across a lowland Amazon regrowth gradient.

Tassiana Maylla Fontoura Caron, Victor Juan Ulises Rodriguez Chuma, Alexander Arévalo Sandi, Darren Norris

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

Tassiana Maylla Fontoura CaronPrograma de Pós-Graduação Em Biodiversidade Tropical, Universidade Federal Do Amapá (UNIFAP), Rod. Juscelino Kubitscheck, Km 02, Macapá, AP, 68902-280, Brazil.
Victor Juan Ulises Rodriguez ChumaFacultad de Ciencias Forestales, Universidad Nacional de La Amazonia Peruana (UNAP), Pevas 5ta cuadra, Iquitos, Peru.
Alexander Arévalo SandiPrograma de Pós-Graduação Em Ecologia, Instituto Nacional de Pesquisas da Amazônia (INPA), Av. André Araújo 2936, Petrópolis, Manaus, AM, 69067-375, Brazil.
Darren NorrisPrograma de Pós-Graduação Em Biodiversidade Tropical, Universidade Federal Do Amapá (UNIFAP), Rod. Juscelino Kubitscheck, Km 02, Macapá, AP, 68902-280, Brazil. dnorris75@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Degraded Amazonian forests can take decades to recover and the ecological results of natural regeneration are still uncertain. Here we use field data collected across 15 lowland Amazon smallholder properties to examine the relationships between forest structure, mammal diversity, regrowth type, regrowth age, topography and hydrology. Forest structure was quantified together with mammal diversity in 30 paired regrowth-control plots. Forest regrowth stage was classified into three groups: late second-regrowth, early second-regrowth and abandoned pasture. Basal area in regrowth plots remained less than half that recorded in control plots even after 20-25 years. Although basal area did increase in sequence from pasture, early to late-regrowth plots, there was a significant decline in basal area of late-regrowth control plots associated with a decline in the proportion of large trees. Variation in different forest structure responses was explained by contrasting variables, with the proportion of small trees (DBH < 20 cm) most strongly explained by topography (altitude and slope) whereas the proportion of large trees (DBH > 60 cm) was explained by plot type (control vs. regrowth) and regrowth class. These findings support calls for increased efforts to actively conserve large trees to avoid retrogressive succession around edges of degraded Amazon forests.

Identifiers

PMID33564057
PMCPMC7873124

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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.