Literature DB >> 27762175

Predictability of helminth parasite host range using information on geography, host traits and parasite community structure.

Tad Dallas1, Andrew W Park1, John M Drake1.   

Abstract

Host-parasite associations are complex interactions dependent on aspects of hosts (e.g. traits, phylogeny or coevolutionary history), parasites (e.g. traits and parasite interactions) and geography (e.g. latitude). Predicting the permissive host set or the subset of the host community that a parasite can infect is a central goal of parasite ecology. Here we develop models that accurately predict the permissive host set of 562 helminth parasites in five different parasite taxonomic groups. We developed predictive models using host traits, host taxonomy, geographic covariates, and parasite community composition, finding that models trained on parasite community variables were more accurate than any other covariate group, even though parasite community covariates only captured a quarter of the variance in parasite community composition. This suggests that it is possible to predict the permissive host set for a given parasite, and that parasite community structure is an important predictor, potentially because parasite communities are interacting non-random assemblages.

Keywords:  FishPEST; boosted regression tree; parasite niche; species distribution model

Mesh:

Year:  2016        PMID: 27762175     DOI: 10.1017/S0031182016001608

Source DB:  PubMed          Journal:  Parasitology        ISSN: 0031-1820            Impact factor:   3.234


  11 in total

1.  What factors explain the geographical range of mammalian parasites?

Authors:  James E Byers; J P Schmidt; Paula Pappalardo; Sarah E Haas; Patrick R Stephens
Journal:  Proc Biol Sci       Date:  2019-05-29       Impact factor: 5.349

2.  What would it take to describe the global diversity of parasites?

Authors:  Colin J Carlson; Tad A Dallas; Laura W Alexander; Alexandra L Phelan; Anna J Phillips
Journal:  Proc Biol Sci       Date:  2020-11-18       Impact factor: 5.349

3.  Characterizing the phylogenetic specialism-generalism spectrum of mammal parasites.

Authors:  A W Park; M J Farrell; J P Schmidt; S Huang; T A Dallas; P Pappalardo; J M Drake; P R Stephens; R Poulin; C L Nunn; T J Davies
Journal:  Proc Biol Sci       Date:  2018-03-14       Impact factor: 5.349

4.  Detecting parasite associations within multi-species host and parasite communities.

Authors:  Tad A Dallas; Anna-Liisa Laine; Otso Ovaskainen
Journal:  Proc Biol Sci       Date:  2019-10-02       Impact factor: 5.349

5.  Food web structure selects for parasite host range.

Authors:  A W Park
Journal:  Proc Biol Sci       Date:  2019-08-14       Impact factor: 5.349

6.  Predicting cryptic links in host-parasite networks.

Authors:  Tad Dallas; Andrew W Park; John M Drake
Journal:  PLoS Comput Biol       Date:  2017-05-25       Impact factor: 4.475

7.  Mapping the Distributions of Mosquitoes and Mosquito-Borne Arboviruses in China.

Authors:  Tao Wang; Zheng-Wei Fan; Yang Ji; Jin-Jin Chen; Guo-Ping Zhao; Wen-Hui Zhang; Hai-Yang Zhang; Bao-Gui Jiang; Qiang Xu; Chen-Long Lv; Xiao-Ai Zhang; Hao Li; Yang Yang; Li-Qun Fang; Wei Liu
Journal:  Viruses       Date:  2022-03-27       Impact factor: 5.818

8.  Linking community assembly and structure across scales in a wild mouse parasite community.

Authors:  Evelyn C Rynkiewicz; Andy Fenton; Amy B Pedersen
Journal:  Ecol Evol       Date:  2019-12-09       Impact factor: 2.912

9.  Mapping ticks and tick-borne pathogens in China.

Authors:  Guo-Ping Zhao; Yi-Xing Wang; Zheng-Wei Fan; Yang Ji; Ming-Jin Liu; Wen-Hui Zhang; Xin-Lou Li; Shi-Xia Zhou; Hao Li; Song Liang; Wei Liu; Yang Yang; Li-Qun Fang
Journal:  Nat Commun       Date:  2021-02-17       Impact factor: 14.919

10.  Testing predictability of disease outbreaks with a simple model of pathogen biogeography.

Authors:  Tad A Dallas; Colin J Carlson; Timothée Poisot
Journal:  R Soc Open Sci       Date:  2019-11-13       Impact factor: 2.963

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