Freshwater and marine indicators of salmon productivity from British Columbia to California and an assessment of risk using climate change projections
Presentation Abstract
Salmon constitute an important indicator of the ecosystem status for the Integrated Ecosystem Assessment (IEA) of the California Current Large Marine Ecosystem (CCLME). Salmon productivity can be affected by freshwater (FW) and marine (M) environments because of their complex life histories that include spawning, rearing, migration, and maturation in both environments. Furthermore, as climate change will likely manifest in different rates of change among environments, it is important to determine how much FW and M indicators are correlated and to what degree we can tease apart their influences on salmon productivity. In this study, we will focus on Pacific Coho and Chinook salmon from southern British Columbia to California. We will test different approaches with three groupings of data: 1) smolts-per-spawner and smolt-to-adult return rates, 2) age-structured adult recruits-per-spawner, and 3) non-age-structured adult returns. As precision in the type of data declines (moving from groupings 1 to 3), our ability to resolve the influences of FW and M indicators on salmon productivity decreases, but the number of datasets available for analysis increases. A comparison of the trade-offs between data quality and quantity will be valuable. The FW and M indicators we are considering include those at the local/regional scale such as water temperature, flow, number of spawners, upwelling, and dissolved oxygen, and those at the large/atmospheric scale such as Pacific Northwest Index, Pacific Decadal Oscillation index, and Southern Oscillation Index. Correlated indicators will be analyzed with multivariate statistical techniques. In various analyses of salmon productivity, we will test whether FW and M indicators (as original values or part of multivariate indices) affect one of the model parameters and the residuals of the Ricker function. Furthermore, we will assess the relative risk of salmon productivity using climate projections in a 20–50 year time frame. Overall, this work will focus on general patterns of environmental indicators of salmon productivity across the coast, and not primarily on determining predictors for specific populations. Identifying which and to what degree FW and M indicators influence salmon productivity and identifying threshold values will be useful for the CCLME-IEA.
Session Title
Session S-08D: Salmon Recovery: Implementation and Progress I
Conference Track
Species and Food Webs
Conference Name
Salish Sea Ecosystem Conference (2014 : Seattle, Wash.)
Document Type
Event
Start Date
1-5-2014 5:00 PM
End Date
1-5-2014 6:30 PM
Location
Room 6C
Genre/Form
conference proceedings; presentations (communicative events)
Contributing Repository
Digital content made available by University Archives, Heritage Resources, Western Libraries, Western Washington University.
Subjects – Topical (LCSH)
Environmental indicators--Salish Sea (B.C. and Wash.); Salmon--Salish Sea (B.C. and Wash.); Ecosystem health--Salish Sea (B.C. and Wash.)
Geographic Coverage
Salish Sea (B.C. and Wash.)
Rights
This resource is displayed for educational purposes only and may be subject to U.S. and international copyright laws. For more information about rights or obtaining copies of this resource, please contact University Archives, Heritage Resources, Western Libraries, Western Washington University, Bellingham, WA 98225-9103, USA (360-650-7534; heritage.resources@wwu.edu) and refer to the collection name and identifier. Any materials cited must be attributed to the Salish Sea Ecosystem Conference Records, University Archives, Heritage Resources, Western Libraries, Western Washington University.
Type
Text
Language
English
Format
application/pdf
Freshwater and marine indicators of salmon productivity from British Columbia to California and an assessment of risk using climate change projections
Room 6C
Salmon constitute an important indicator of the ecosystem status for the Integrated Ecosystem Assessment (IEA) of the California Current Large Marine Ecosystem (CCLME). Salmon productivity can be affected by freshwater (FW) and marine (M) environments because of their complex life histories that include spawning, rearing, migration, and maturation in both environments. Furthermore, as climate change will likely manifest in different rates of change among environments, it is important to determine how much FW and M indicators are correlated and to what degree we can tease apart their influences on salmon productivity. In this study, we will focus on Pacific Coho and Chinook salmon from southern British Columbia to California. We will test different approaches with three groupings of data: 1) smolts-per-spawner and smolt-to-adult return rates, 2) age-structured adult recruits-per-spawner, and 3) non-age-structured adult returns. As precision in the type of data declines (moving from groupings 1 to 3), our ability to resolve the influences of FW and M indicators on salmon productivity decreases, but the number of datasets available for analysis increases. A comparison of the trade-offs between data quality and quantity will be valuable. The FW and M indicators we are considering include those at the local/regional scale such as water temperature, flow, number of spawners, upwelling, and dissolved oxygen, and those at the large/atmospheric scale such as Pacific Northwest Index, Pacific Decadal Oscillation index, and Southern Oscillation Index. Correlated indicators will be analyzed with multivariate statistical techniques. In various analyses of salmon productivity, we will test whether FW and M indicators (as original values or part of multivariate indices) affect one of the model parameters and the residuals of the Ricker function. Furthermore, we will assess the relative risk of salmon productivity using climate projections in a 20–50 year time frame. Overall, this work will focus on general patterns of environmental indicators of salmon productivity across the coast, and not primarily on determining predictors for specific populations. Identifying which and to what degree FW and M indicators influence salmon productivity and identifying threshold values will be useful for the CCLME-IEA.
