Asset Details
Do you wish to reserve the book?
Assessment modelling approaches for stocks with spawning components, seasonal and spatial dynamics, and limited resources for data collection
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Assessment modelling approaches for stocks with spawning components, seasonal and spatial dynamics, and limited resources for data collection
Do you wish to request the book?
Assessment modelling approaches for stocks with spawning components, seasonal and spatial dynamics, and limited resources for data collection
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Assessment modelling approaches for stocks with spawning components, seasonal and spatial dynamics, and limited resources for data collection
2019
Overview
The true spatiotemporal structure of a fish population is often more complex than represented in assessments because movement between spawning components is disregarded and data at the necessary scale are unavailable. This can generate poor advice. We explore the impacts of modelling choices and their associated risks given limited data and lack of biological knowledge on spawning component structure and connectivity. Pseudo-data for an age structured fish population were simulated with two spawning components that experience various levels of connectivity and that might overlap during a certain period but segregate during reproduction. A variety of implicit spatiotemporal and simpler models were fitted to the pseudo-datasets, mimicking different situations of data availability. To reproduce the true stock characteristics, the spatiotemporal models required total catch data disaggregated by spawning component; however, catch-at-age was not as important nor were disaggregated biomass indices to reproduce true dynamics. Even with just 5% connectivity between spawning components, both the spatiotemporal models and simpler alternatives generally overestimated stock biomass. Although bias was smallest when considering one unit population, spawning components might still need to be considered for management and conservation. In such case, the spatiotemporal model was less influenced by ignored connectivity patterns compared to a model focussing on one spawning component only.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ Biomass
/ Computer and Information Sciences
/ Fish
/ Fishes
/ Fishing
/ Mimicry
/ Research and Analysis Methods
/ Seasons
/ Spawning
/ Stocks
