Tapeworm discovery in elasmobranch fishes: quantifying patterns and identifying their correlates

2020 ◽  
Vol 71 (1) ◽  
pp. 78 ◽  
Author(s):  
Haseeb S. Randhawa ◽  
Robert Poulin

Most parasites from known host species are yet to be discovered and described, let alone those from host species not yet known to science. Here, we use tapeworms of elasmobranchs to identify factors influencing their discovery and explaining the time lag between the descriptions of elasmobranch hosts and their respective tapeworm parasites. The dataset included 918 tapeworm species from 290 elasmobranch species. Data were analysed using linear mixed-effects models. Our findings indicated that we are currently in the midst of the greatest rate of discovery for tapeworms exploiting elasmobranchs. We identified tapeworm size, year of discovery of the type host, host latitudinal range and type locality of the parasite influencing most on the probability of discovery of tapeworms from elasmobranchs and the average time lag between descriptions of elasmobranchs and their tapeworms. The time lag between descriptions is decreasing progressively, but, at current rates and number of taxonomic experts, it will take two centuries to clear the backlog of undescribed tapeworms from known elasmobranch species. Given that the number of new elasmobranch species described each year is on the rise, we need to re-assess funding strategies to save elasmobranchs (and, thus, their tapeworm parasites) before they go extinct.

2021 ◽  
pp. 001316442199489
Author(s):  
Luyao Peng ◽  
Sandip Sinharay

Wollack et al. (2015) suggested the erasure detection index (EDI) for detecting fraudulent erasures for individual examinees. Wollack and Eckerly (2017) and Sinharay (2018) extended the index of Wollack et al. (2015) to suggest three EDIs for detecting fraudulent erasures at the aggregate or group level. This article follows up on the research of Wollack and Eckerly (2017) and Sinharay (2018) and suggests a new aggregate-level EDI by incorporating the empirical best linear unbiased predictor from the literature of linear mixed-effects models (e.g., McCulloch et al., 2008). A simulation study shows that the new EDI has larger power than the indices of Wollack and Eckerly (2017) and Sinharay (2018). In addition, the new index has satisfactory Type I error rates. A real data example is also included.


2021 ◽  
pp. 1-4
Author(s):  
Michaela Kranepuhl ◽  
Detlef May ◽  
Edna Hillmann ◽  
Lorenz Gygax

Abstract This research communication describes the relationship between the occurrence of lameness and body condition score (BCS) in a sample of 288 cows from a single farm that were repeatedly scored in the course of 9 months while controlling for confounding variables. The relationship between BCS and lameness was evaluated using generalised linear mixed-effects models. It was found that the proportion of lame cows was higher with decreasing but also with increasing BCS, increased with lactation number and decreased with time since the last claw trimming. This is likely to reflect the importance of sufficient body condition in the prevention of lameness but also raises the question of the impact of overcondition on lameness and the influence of claw trimming events on the assessment of lameness. A stronger focus on BCS might allow improved management of lameness that is still one of the major problems in housed cows.


2007 ◽  
Vol 27 (14) ◽  
pp. 2586-2600 ◽  
Author(s):  
Fetene B. Tekle ◽  
Frans E. S. Tan ◽  
Martijn P. F. Berger

Biostatistics ◽  
2012 ◽  
Vol 14 (1) ◽  
pp. 144-159 ◽  
Author(s):  
R. Drikvandi ◽  
G. Verbeke ◽  
A. Khodadadi ◽  
V. Partovi Nia

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