Evidence map›Paper›PMID 37490227›Full record

ArticleAmbio2024

The historical trajectory of a coffee agri-food system: A case study in Oaxaca, Mexico.

Alejandra Ramírez-León, Veronique Sophie Avila-Foucat, Driss Ezzine-de-Blas

Abstract readHistorical Article
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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Alejandra Ramírez-LeónPostgraduate of Sustainability Sciences, National Autonomous University of Mexico (UNAM), Oriente 163 Número 234, Col. Campestre Aragón, Alcaldía Gustavo A. Madero, C.P. 07530, Mexico City, México. aramirezl@comunidad.unam.mx.ORCID http://orcid.org/0000-0001-9770-0860
Veronique Sophie Avila-FoucatEconomics Research Institute and National Coastal Resilience Laboratory, National Autonomous University of Mexico (UNAM), Circuito Mario de la Cueva, Ciudad de la Investigación en Humanidades, Ciudad Universitaria, C.P. 04510, Mexico City, México.
Driss Ezzine-de-BlasCentre de Coopération Internationale en Recherche Agronomique Pour le Développement (CIRAD), Montpellier, France.

Funding

Agence Nationale de la Recherche 290832Consejo Nacional de Ciencia y Tecnología 290832Universidad Nacional Autónoma de México PAPIIT-IN302720
6 · The paper itself

Abstract

Agri-food social-ecological systems (AFSES) embrace complex interactions and processes of food production, processing, and commercialization that are subject to constant changes. This study develops a heuristic approach using the adaptive cycle (AC) and a transformation potential measure to identify the historical trajectory of a coffee AFSES at a watershed scale in Copalita, Mexico, over 40 years from 1980 to 2020. Primary information was collected through semistructured interviews. The results show that the system interactions depend on economic, social, and environmental stressors and shocks affecting different temporal and spatial scales. The cumulative effects of driving forces and adaptive strategies have influenced the system to not complete the AC phases. Additionally, the results show that some adaptive strategies can become new stressors with time. Driving forces, adaptive strategies, tipping points, trade-offs and interactions within the AFSES could be identified as the main aspects defining system resilience.

Indexed as

CoffeeAgricultureFood SupplyMexicoCoffeeAdaptive cycleAdaptive strategiesAgri-food systemsCoffeeHistorical trajectorySocial–ecological systems

Identifiers

PMID37490227
PMCPMC11568096

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.