Monitoring change in a dynamic environment: spatiotemporal modelling of calibrated data from different types of fisheries surveys of Pacific halibut
Monitoring distributional shifts in Arctic and subarctic fish species as environmental conditions change can be difficult due to sparse or infrequent surveys. Pacific halibut (Hippoglossus stenolepis) are found as far north as the Bering Strait, and future changes in sea temperatures and prey distri...
Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Canadian Science Publishing
2020
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1139/cjfas-2019-0240 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2019-0240 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2019-0240 |
Summary: | Monitoring distributional shifts in Arctic and subarctic fish species as environmental conditions change can be difficult due to sparse or infrequent surveys. Pacific halibut (Hippoglossus stenolepis) are found as far north as the Bering Strait, and future changes in sea temperatures and prey distribution may lead to an expanded range. For this and other species, it is therefore important to use as much survey data as is available when estimating density indices and other quantities of interest. Setline and trawl surveys in the eastern Bering Sea provide partial coverage each year, but the two gear types capture different size distributions of fish. We apply a calibration method to data from the setline and trawl surveys to produce consistent, spatially indexed estimates of indices of local density. The resulting estimates are then combined through spatiotemporal models that can incorporate environmental covariates to provide reliable density indices and to map the dynamic distribution of Pacific halibut. Such approaches may become increasingly important as climate change affects species distribution relative to historical survey footprints, and scientists must adapt to the use of new and variable data sources. |
---|