Variation in pre-treatment count lead time and its effect on baseline estimates of cage-level sea lice abundance
Gautam, R and Boerlage, A S and Vanderstichel, R and Revie, C W and Hammell, K L (2016) Variation in pre-treatment count lead time and its effect on baseline estimates of cage-level sea lice abundance. Journal of Fish Diseases, 39 (11). pp. 1297-1303. ISSN 0140-7775 (https://doi.org/10.1111/jfd.12460)
Preview |
Text.
Filename: Gautam_etal_JFD_2016_Variations_in_pre_treatment_count_lead_time.pdf
Accepted Author Manuscript Download (579kB)| Preview |
Abstract
Treatment efficacy studies typically use pre-treatment sea lice abundance as the baseline. However, the pre-treatment counting window often varies from the day of treatment to several days before treatment. We assessed the effect of lead time on baseline estimates, using historical data (2010-14) from a sea lice data management programme (Fish-iTrends). Data were aggregated at the cage level for three life stages: (i) chalimus, (ii) pre-adult and adult male and (iii) adult female. Sea lice counts were log-transformed, and mean counts by lead time relative to treatment day were computed and compared separately for each life stage, using linear mixed models. There were 1,658 observations (treatment events) from 56 sites in 5 Bay Management Areas. Our study showed that lead time had a significant effect on the estimated sea lice abundance, which was moderated by season. During the late summer and autumn periods, counting on the day of treatment gave significantly higher values than other days and would be a more appropriate baseline estimate, while during spring and early summer abundance estimates were comparable among counts within 5 days of treatment. A season-based lead time window may be most appropriate when estimating baseline sea lice levels.
ORCID iDs
Gautam, R, Boerlage, A S, Vanderstichel, R, Revie, C W ORCID: https://orcid.org/0000-0002-5018-0340 and Hammell, K L;-
-
Item type: Article ID code: 64879 Dates: DateEvent30 November 2016Published24 February 2016Published Online21 December 2015AcceptedSubjects: Agriculture > Aquaculture. Fisheries. Angling Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 26 Jul 2018 13:58 Last modified: 11 Nov 2024 12:00 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/64879