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Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples

Ensembles of Species Distribution Models (SDMs) represent the geographic ranges of pathogen vectors by combining alternative analytical approaches and merging information on vector occurrences with more extensive environmental data. Biased collection data impact SDMs, regardless of the target specie...

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Autores principales: Kessler, William H., De Jesus, Carrie, Wisely, Samantha M., Glass, Gregory E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222110/
https://www.ncbi.nlm.nih.gov/pubmed/35735632
http://dx.doi.org/10.3390/diseases10020032
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author Kessler, William H.
De Jesus, Carrie
Wisely, Samantha M.
Glass, Gregory E.
author_facet Kessler, William H.
De Jesus, Carrie
Wisely, Samantha M.
Glass, Gregory E.
author_sort Kessler, William H.
collection PubMed
description Ensembles of Species Distribution Models (SDMs) represent the geographic ranges of pathogen vectors by combining alternative analytical approaches and merging information on vector occurrences with more extensive environmental data. Biased collection data impact SDMs, regardless of the target species, but no studies have compared the differences in the distributions predicted by the ensemble models when different sampling frameworks are used for the same species. We compared Ensemble SDMs for two important Ixodid tick vectors, Amblyomma americanum and Ixodes scapularis in mainland Florida, USA, when inputs were either convenience samples of ticks, or collections obtained using the standard protocols promulgated by the U.S. Centers for Disease Control and Prevention. The Ensemble SDMs for the convenience samples and standard surveys showed only a slight agreement (Kappa = 0.060, A. americanum; 0.053, I. scapularis). Convenience sample SDMs indicated A. americanum and I. scapularis should be absent from nearly one third (34.5% and 30.9%, respectively) of the state where standard surveys predicted the highest likelihood of occurrence. Ensemble models from standard surveys predicted 81.4% and 72.5% (A. americanum and I. scapularis) of convenience sample sites. Omission errors by standard survey SDMs of the convenience collections were associated almost exclusively with either adjacency to at least one SDM, or errors in geocoding algorithms that failed to correctly locate geographic locations of convenience samples. These errors emphasize commonly overlooked needs to explicitly evaluate and improve data quality for arthropod survey data that are applied to spatial models.
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spelling pubmed-92221102022-06-24 Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples Kessler, William H. De Jesus, Carrie Wisely, Samantha M. Glass, Gregory E. Diseases Article Ensembles of Species Distribution Models (SDMs) represent the geographic ranges of pathogen vectors by combining alternative analytical approaches and merging information on vector occurrences with more extensive environmental data. Biased collection data impact SDMs, regardless of the target species, but no studies have compared the differences in the distributions predicted by the ensemble models when different sampling frameworks are used for the same species. We compared Ensemble SDMs for two important Ixodid tick vectors, Amblyomma americanum and Ixodes scapularis in mainland Florida, USA, when inputs were either convenience samples of ticks, or collections obtained using the standard protocols promulgated by the U.S. Centers for Disease Control and Prevention. The Ensemble SDMs for the convenience samples and standard surveys showed only a slight agreement (Kappa = 0.060, A. americanum; 0.053, I. scapularis). Convenience sample SDMs indicated A. americanum and I. scapularis should be absent from nearly one third (34.5% and 30.9%, respectively) of the state where standard surveys predicted the highest likelihood of occurrence. Ensemble models from standard surveys predicted 81.4% and 72.5% (A. americanum and I. scapularis) of convenience sample sites. Omission errors by standard survey SDMs of the convenience collections were associated almost exclusively with either adjacency to at least one SDM, or errors in geocoding algorithms that failed to correctly locate geographic locations of convenience samples. These errors emphasize commonly overlooked needs to explicitly evaluate and improve data quality for arthropod survey data that are applied to spatial models. MDPI 2022-06-08 /pmc/articles/PMC9222110/ /pubmed/35735632 http://dx.doi.org/10.3390/diseases10020032 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kessler, William H.
De Jesus, Carrie
Wisely, Samantha M.
Glass, Gregory E.
Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples
title Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples
title_full Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples
title_fullStr Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples
title_full_unstemmed Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples
title_short Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples
title_sort ensemble models for tick vectors: standard surveys compared with convenience samples
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222110/
https://www.ncbi.nlm.nih.gov/pubmed/35735632
http://dx.doi.org/10.3390/diseases10020032
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