Evidence map›Paper›PMID 32314042›Full record

ArticleOecologia2020

Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection.

José Wagner Ribeiro, Tadeu Siqueira, Graziella V DiRenzo, Carolina Lambertini, Mariana L Lyra, Luís Felipe Toledo, Célio F B Haddad, C Guilherme Becker

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Oecologia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. 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

8 authors at 4 institutions in 2 countries.

José Wagner RibeiroInstituto de Biociências, Universidade Estadual Paulista (Unesp), Av. 24A 1515, Rio Claro, São Paulo, 13506-900, Brazil. jwribeirojunior@gmail.com.ORCID http://orcid.org/0000-0003-3438-6936
Tadeu SiqueiraInstituto de Biociências, Universidade Estadual Paulista (Unesp), Av. 24A 1515, Rio Claro, São Paulo, 13506-900, Brazil.
Graziella V DiRenzoDepartment of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA, 93106, USA.
Carolina LambertiniLaboratório de História Natural de Anfíbios Brasileiros (LaHNAB), Departamento de Biologia Animal, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, SP, 13083-862, Brazil.
Mariana L LyraInstituto de Biociências, Universidade Estadual Paulista (Unesp), Av. 24A 1515, Rio Claro, São Paulo, 13506-900, Brazil.
Luís Felipe ToledoLaboratório de História Natural de Anfíbios Brasileiros (LaHNAB), Departamento de Biologia Animal, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, SP, 13083-862, Brazil.
Célio F B HaddadDepartamento de Biodiversidade e Centro de Aquicultura (CAUNESP), Instituto de Biociências, Universidade Estadual Paulista (Unesp), Rio Claro, São Paulo, 13506-900, Brazil.
C Guilherme BeckerDepartment of Biological Sciences, The University of Alabama, Tuscaloosa, AL, 35487, USA.
Universidade Estadual Paulista (Unesp) · BRUniversidade Estadual de Campinas (UNICAMP) · BRUniversity of Alabama · USUniversity of California, Santa Barbara · US

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 300896/2016-6Fundação de Amparo à Pesquisa do Estado de São Paulo 2013/50424-1Fundação de Amparo à Pesquisa do Estado de São Paulo 2014/07113-8Fundação de Amparo à Pesquisa do Estado de São Paulo 2016/07469-2Fundação de Amparo à Pesquisa do Estado de São Paulo 2016/25358-3National Science Foundation 1611692Rufford Foundation 16419-1
6 · The paper itself

Abstract

Ecologists studying emerging wildlife diseases need to confront the realism of imperfect pathogen detection across heterogeneous habitats to aid in conservation decisions. For example, spatial risk assessments of amphibian disease caused by Batrachochytrium dendrobatidis (Bd) has largely ignored imperfect pathogen detection across sampling sites. Because changes in pathogenicity and host susceptibility could trigger recurrent population declines, it is imperative to understand how pathogen prevalence and occupancy vary across environmental gradients. Here, we assessed how Bd occurrence, prevalence, and infection intensity in a diverse Neotropical landscape vary across streams in relation to abiotic and biotic predictors using a hierarchical Bayesian model that accounts for imperfect Bd detection caused by qPCR error. Our model indicated that the number of streams harboring Bd-infected frogs is higher than observed, with Bd likely being present at ~ 43% more streams than it was detected. We found that terrestrial-breeders captured along streams had higher Bd prevalence, but lower infection intensity, than aquatic-breeding species. We found a positive relationship between Bd occupancy probability and stream density, and a negative relationship between Bd occupancy probability and amphibian local richness. Forest cover was a weak predictor of Bd occurrence and infection intensity. Finally, we provide estimates for the minimum number of amphibian captures needed to determine the presence of Bd at a given site where Bd occurs, thus, providing guidence for cost-effective disease risk monitoring programs.

Indexed as

ChytridiomycotaRiversAmphibiansAnimalsAnuraBayes TheoremEcosystemAmphibian diseaseAtlantic forestBatrachochytrium dendrobatidisBayesian hierarchical modelTropical streams

Identifiers

PMID32314042
OpenAlexW3016340685

What OpenQuestion holds

Textmetadata
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.