2017 journal article
Estimating Fish Mortality Rates Using Telemetry and Multistate Models
FISHERIES, 42(4), 210–219.
TL;DR:
Estimates generally appeared to be unbiased for a simulated study with five periods and releases of telemetered fish at the start of periods 1–4 and larger sample sizes are needed to achieve reliable estimates of component rates.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(OpenAlex)
14. Life Below Water
(Web of Science)
15. Life on Land
(Web of Science)
Source: Web Of Science
Added: August 6, 2018
We simulated and evaluated multistate capture–recapture models to estimate mortality rates using telemetry data. Four field designs were considered: (A) fixed receivers to estimate total instantaneous mortality (Z), (B) manual searches to estimate instantaneous fishing (F) and natural (M) mortality, (C) fixed receivers combined with external high‐reward tags to estimate F and M, and (D) manual searches combined with external high‐reward tags to estimate M and fishing mortality rates associated with harvest (Fh) and catch‐and‐release death (Fcr) as well as the probability of death due to catch and release (α). Estimates generally appeared to be unbiased for a simulated study with five periods and releases of telemetered fish at the start of periods 1–4. Compared to estimating Z, larger sample sizes are needed to achieve reliable estimates of component rates (F and M). Estimates of component rates were more precise when that source of mortality was directly observed (M in design B, F in design C). The field design using fixed receivers and high‐reward tags should be especially useful in practice, because manual searches are not required to estimate F and M. Multistate models are useful for clarifying the connection between field observations and ecological processes. Reliable estimates of mortality rates, coupled with information on behavior, habitat use, and movement, make telemetry a highly valuable tool for improving fisheries management and stock assessment.
