Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/s00442-020-04646-4 http://hdl.handle.net/11449/200355 |
Resumo: | 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. |
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Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detectionAmphibian diseaseAtlantic forestBatrachochytrium dendrobatidisBayesian hierarchical modelTropical streamsEcologists 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.National Science FoundationRufford FoundationFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Instituto de Biociências Universidade Estadual Paulista (Unesp), Av. 24A 1515Department of Ecology Evolution and Marine Biology University of CaliforniaLaboratório de História Natural de Anfíbios Brasileiros (LaHNAB) Departamento de Biologia Animal Instituto de Biologia Universidade Estadual de CampinasDepartamento de Biodiversidade e Centro de Aquicultura (CAUNESP) Instituto de Biociências Universidade Estadual Paulista (Unesp)Department of Biological Sciences The University of AlabamaInstituto de Biociências Universidade Estadual Paulista (Unesp), Av. 24A 1515Departamento de Biodiversidade e Centro de Aquicultura (CAUNESP) Instituto de Biociências Universidade Estadual Paulista (Unesp)National Science Foundation: 1611692Rufford Foundation: 16419-1FAPESP: 2013/50424-1FAPESP: 2014/07113-8FAPESP: 2016/07469-2FAPESP: 2016/25358-3CNPq: 300896/2016-6Universidade Estadual Paulista (Unesp)University of CaliforniaUniversidade Estadual de Campinas (UNICAMP)The University of AlabamaRibeiro, José Wagner [UNESP]Siqueira, Tadeu [UNESP]DiRenzo, Graziella V.Lambertini, CarolinaLyra, Mariana L. [UNESP]Toledo, Luís FelipeHaddad, Célio F. B. [UNESP]Becker, C. Guilherme2020-12-12T02:04:27Z2020-12-12T02:04:27Z2020-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article237-248http://dx.doi.org/10.1007/s00442-020-04646-4Oecologia, v. 193, n. 1, p. 237-248, 2020.1432-19390029-8549http://hdl.handle.net/11449/20035510.1007/s00442-020-04646-42-s2.0-85084067659Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengOecologiainfo:eu-repo/semantics/openAccess2024-04-09T15:29:47Zoai:repositorio.unesp.br:11449/200355Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:45:52.319452Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection |
title |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection |
spellingShingle |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection Ribeiro, José Wagner [UNESP] Amphibian disease Atlantic forest Batrachochytrium dendrobatidis Bayesian hierarchical model Tropical streams |
title_short |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection |
title_full |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection |
title_fullStr |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection |
title_full_unstemmed |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection |
title_sort |
Assessing amphibian disease risk across tropical streams while accounting for imperfect pathogen detection |
author |
Ribeiro, José Wagner [UNESP] |
author_facet |
Ribeiro, José Wagner [UNESP] Siqueira, Tadeu [UNESP] DiRenzo, Graziella V. Lambertini, Carolina Lyra, Mariana L. [UNESP] Toledo, Luís Felipe Haddad, Célio F. B. [UNESP] Becker, C. Guilherme |
author_role |
author |
author2 |
Siqueira, Tadeu [UNESP] DiRenzo, Graziella V. Lambertini, Carolina Lyra, Mariana L. [UNESP] Toledo, Luís Felipe Haddad, Célio F. B. [UNESP] Becker, C. Guilherme |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) University of California Universidade Estadual de Campinas (UNICAMP) The University of Alabama |
dc.contributor.author.fl_str_mv |
Ribeiro, José Wagner [UNESP] Siqueira, Tadeu [UNESP] DiRenzo, Graziella V. Lambertini, Carolina Lyra, Mariana L. [UNESP] Toledo, Luís Felipe Haddad, Célio F. B. [UNESP] Becker, C. Guilherme |
dc.subject.por.fl_str_mv |
Amphibian disease Atlantic forest Batrachochytrium dendrobatidis Bayesian hierarchical model Tropical streams |
topic |
Amphibian disease Atlantic forest Batrachochytrium dendrobatidis Bayesian hierarchical model Tropical streams |
description |
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. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-12T02:04:27Z 2020-12-12T02:04:27Z 2020-05-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1007/s00442-020-04646-4 Oecologia, v. 193, n. 1, p. 237-248, 2020. 1432-1939 0029-8549 http://hdl.handle.net/11449/200355 10.1007/s00442-020-04646-4 2-s2.0-85084067659 |
url |
http://dx.doi.org/10.1007/s00442-020-04646-4 http://hdl.handle.net/11449/200355 |
identifier_str_mv |
Oecologia, v. 193, n. 1, p. 237-248, 2020. 1432-1939 0029-8549 10.1007/s00442-020-04646-4 2-s2.0-85084067659 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Oecologia |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
237-248 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1808128854979510272 |