Evidence map›Paper›PMID 35770837›Full record

ReviewGlobal change biology2022

Feedback in tropical forests of the Anthropocene.

Bernardo M Flores, Arie Staal

Abstract readReview
In one paragraph

Review in Global change biology, 2022. 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. Review
  2. Article
  3. Critical slowing down of the Amazon forest after increased drought occurrence.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Review
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.

Bernardo M FloresGraduate Program in Ecology, Federal University of Santa Catarina, Florianopolis, Brazil.ORCID 0000-0003-4555-5598
Arie StaalCopernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0001-5409-1436

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tropical forests are complex systems containing myriad interactions and feedbacks with their biotic and abiotic environments, but as the world changes fast, the future of these ecosystems becomes increasingly uncertain. In particular, global stressors may unbalance the feedbacks that stabilize tropical forests, allowing other feedbacks to propel undesired changes in the whole ecosystem. Here, we review the scientific literature across various fields, compiling known interactions of tropical forests with their environment, including the global climate, rainfall, aerosols, fire, soils, fauna, and human activities. We identify 170 individual interactions among 32 elements that we present as a global tropical forest network, including countless feedback loops that may emerge from different combinations of interactions. We illustrate our findings with three cases involving urgent sustainability issues: (1) wildfires in wetlands of South America; (2) forest encroachment in African savanna landscapes; and (3) synergistic threats to the peatland forests of Borneo. Our findings reveal an unexplored world of feedbacks that shape the dynamics of tropical forests. The interactions and feedbacks identified here can guide future qualitative and quantitative research on the complexities of tropical forests, allowing societies to manage the nonlinear responses of these ecosystems in the Anthropocene.

Indexed as

EcosystemFiresFeedbackForestsHumansTreesTropical ClimateAmazon forestAnthropoceneclimate changeCongo forestresilienceSocial-ecological systemsSoutheast Asian forests

Identifiers

PMID35770837
PMCPMC9542052

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.