2021
DOI: 10.1002/ecs2.3709
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Weighing the predictors: host traits and coinfecting species both explain variation in parasitism of Rock Ptarmigan

Abstract: Testing hypotheses in ecological and evolutionary parasitology can require testing whether host traits or coinfecting parasites explain variation in parasitism by focal species. However, when host traits and coinfecting parasites are considered separately, relations between either and parasitism by focal species can be spurious—a problem that is addressed when both are considered together. We assessed whether abundances of focal parasites related to host age/sex and coinfecting parasites for three endoparasite… Show more

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Cited by 3 publications
(5 citation statements)
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References 51 publications
(119 reference statements)
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“…In the present study, for example, we could not look at the relationship between host age or sex and aggregation for each parasite species, because such stratification would result in different numbers of samples across models (one sample per species per year, vs. two or four if one or both host-level variables were also considered). We could not address whether any potential associations between co-infecting parasites explained patterns of aggregation, as such modeling would necessarily apply exclusively to individual host-level data; however, we do not expect co-infection to impact aggregation in this system as previous research demonstrated that any associations between these parasites explained on average only 2.01% of the observed variation in abundance, and never more than 5.13% ( Morrill et al, 2021 ). To answer those questions regarding host-level predictors of aggregation or co-infection, an alternative modeling approach with a multivariate response could be used that considers parasite abundances for each species as following, for example, negative binomial (Poisson-Gamma mixture) distributions, that then additionally estimates the distributions’ dispersion parameters.…”
Section: Discussionmentioning
confidence: 97%
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“…In the present study, for example, we could not look at the relationship between host age or sex and aggregation for each parasite species, because such stratification would result in different numbers of samples across models (one sample per species per year, vs. two or four if one or both host-level variables were also considered). We could not address whether any potential associations between co-infecting parasites explained patterns of aggregation, as such modeling would necessarily apply exclusively to individual host-level data; however, we do not expect co-infection to impact aggregation in this system as previous research demonstrated that any associations between these parasites explained on average only 2.01% of the observed variation in abundance, and never more than 5.13% ( Morrill et al, 2021 ). To answer those questions regarding host-level predictors of aggregation or co-infection, an alternative modeling approach with a multivariate response could be used that considers parasite abundances for each species as following, for example, negative binomial (Poisson-Gamma mixture) distributions, that then additionally estimates the distributions’ dispersion parameters.…”
Section: Discussionmentioning
confidence: 97%
“…Assuming the ecto-/endoparasite dichotomy with respect to relationships between aggregation and mean abundance is real, we should consider broad differences in traits between these groups of parasites other than the leading explanations of differences in niche capacity and density-dependent transmission. Transmission of ectoparasites between hosts is expected particularly during brood-rearing and crêche formation ( Nielsen et al, 2020 ) and is expected to be mediated by the louse fly for certain parasites ( Morrill et al, 2021 ). One broad difference between parasite types concerns variation in factors affecting the viability or availability of infective stages.…”
Section: Discussionmentioning
confidence: 99%
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“…In the present study, for example, we could not look at the relationship between host age or sex and aggregation for each parasite species, because such stratification would result in different numbers of samples across models (one sample per species per year, vs. two or four if one or both host-level variables were also considered). We could not address whether any potential associations between co-infecting parasites explained patterns of aggregation, as such modeling would necessarily apply exclusively to individual host-level data; however, we do not expect coinfection to impact aggregation in this system as previous research demonstrated that any associations between these parasites explained on average only 2.01% of the observed variation in abundance, and never more than 5.13% (Morrill et al, 2021). To answer those questions regarding host-level predictors of aggregation or co-infection, an alternative modeling approach with a multivariate response could be used that considers parasite abundances for each species as following, for example, negative binomial (Poisson-Gamma mixture) distributions, that then additionally estimates the distributions' dispersion parameters.…”
Section: Discussionmentioning
confidence: 97%
“…Icelandic Rock Ptarmigan (Lagopus muta, hereafter ptarmigan) are an ideal host species to study parasite aggregation because they have been subject to intense research as a game bird and have provided large numbers of replicates for ecological studies(Morrill et al, 2021;Nielsen et al, 2020;Stenkewitz et al, 2016); additionally, their parasite fauna are exceptionally well known and can be sampled with standardized protocols(Skírnisson, Thorarinsdottir & …”
mentioning
confidence: 99%