Evidence map›Paper›PMID 29933391›Full record

ArticlePloS one2018

Prediction of insect pest distribution as influenced by elevation: Combining field observations and temperature-dependent development models for the coffee stink bug, Antestiopsis thunbergii (Gmelin).

Abdelmutalab G A Azrag, Christian W W Pirk, Abdullahi A Yusuf, Fabrice Pinard, Saliou Niassy, Gladys Mosomtai, Régis Babin

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Potential distribution prediction ofEcology and evolution · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. 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

7 authors.

Abdelmutalab G A AzragInternational Centre of Insect Physiology and Ecology, Nairobi, Kenya.ORCID 0000-0002-2192-3803
Christian W W PirkDepartment of Zoology and Entomology, University of Pretoria, Pretoria, South Africa.
Abdullahi A YusufDepartment of Zoology and Entomology, University of Pretoria, Pretoria, South Africa.
Fabrice PinardUPR Bioagresseurs, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Nairobi, Kenya.
Saliou NiassyInternational Centre of Insect Physiology and Ecology, Nairobi, Kenya.
Gladys MosomtaiInternational Centre of Insect Physiology and Ecology, Nairobi, Kenya.
Régis BabinInternational Centre of Insect Physiology and Ecology, Nairobi, Kenya.ORCID 0000-0002-3753-1193

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The antestia bug, Antestiopsis thunbergii (Gmelin 1790) is a major pest of Arabica coffee in Africa. The bug prefers coffee at the highest elevations, contrary to other major pests. The objectives of this study were to describe the relationship between A. thunbergii populations and elevation, to elucidate this relationship using our knowledge of the pest thermal biology and to predict the pest distribution under climate warming. Antestiopsis thunbergii population density was assessed in 24 coffee farms located along a transect delimited across an elevation gradient in the range 1000-1700 m asl, on Mt. Kilimanjaro, Tanzania. Density was assessed for three different climatic seasons, the cool dry season in June 2014 and 2015, the short rainy season in October 2014 and the warm dry season in January 2015. The pest distribution was predicted over the same transect using three risk indices: the establishment risk index (ERI), the generation index (GI) and the activity index (AI). These indices were computed using simulated life table parameters obtained from temperature-dependent development models and temperature data from 1) field records using data loggers deployed over the transect and 2) predictions for year 2055 extracted from AFRICLIM database. The observed population density was the highest during the cool dry season and increased significantly with increasing elevation. For current temperature, the ERI increased with an increase in elevation and was therefore distributed similarly to observed populations, contrary to the other indices. This result suggests that immature stage susceptibility to extreme temperatures was a key factor of population distribution as impacted by elevation. In the future, distribution of the risk indices globally indicated a decrease of the risk at low elevation and an increase of the risk at the highest elevations. Based on these results, we concluded with recommendations to mitigate the risk of A. thunbergii infestation.

Indexed as

AltitudeAnimal DistributionHemipteraModels, TheoreticalTemperatureAgricultureAnimalsClimateCoffeaComputer SimulationRiskTanzania

Identifiers

PMID29933391
PMCPMC6014636

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.