The effects of environmental factors on the migratory movement patterns of Sacramento River yearling late-fall run Chinook salmon (Oncorhynchus tshawytscha)

被引:38
|
作者
Michel, Cyril J. [1 ]
Ammann, Arnold J. [1 ]
Chapman, Eric D. [2 ]
Sandstrom, Philip T. [2 ]
Fish, Heidi E. [1 ]
Thomas, Michael J. [2 ]
Singer, Gabriel P. [2 ]
Lindley, Steven T. [1 ]
Klimley, A. Peter [2 ]
MacFarlane, R. Bruce [1 ]
机构
[1] NOAA, Fisheries Ecol Div, SW Fisheries Sci Ctr, Natl Marine Fisheries Serv, Santa Cruz, CA 95060 USA
[2] Univ Calif Davis, Biotelemetry Lab, Dept Wildlife Fish & Conservat Biol, Davis, CA 95616 USA
关键词
Environmental factors; Migration; Acoustic telemetry; Smolt; Chinook salmon; Sacramento River; Biotelemetry; TRAVEL-TIME; SURVIVAL; BEHAVIOR; SMOLTS; STEELHEAD; MODEL;
D O I
10.1007/s10641-012-9990-8
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Understanding smolt migration dynamics is a critical step in the preservation and conservation of imperiled salmonids in California's Sacramento River system. Late-fall run Chinook salmon yearling smolts were acoustically tagged and tracked during their outmigration through California's Sacramento River and San Francisco Estuary during 2007-2009. Migration rates were 14.3 km center dot day(-1) (+/- 1.3 S.E.) to 23.5 kma (TM) day(-1) (+/- 3.6 S.E.), similar to rates published for other West Coast yearling Chinook salmon smolt emigrations. Region-specific movement rates were fastest through the upper river regions, and slowest in the Sacramento/San Joaquin River Delta. River travel times were recorded for smolts travelling through a series of ten monitor-delimited reaches. Using these, a smolt travel time model determined by two parameters (movement rate and rate of population spreading) was then used to determine the influence of different factors on the model's fit, using model selection with Akaike's Information Criterion. The model that allowed for both year and reach to be expressed additively for both travel time and population spreading rate estimates, while accounting for a "release" effect, was the best supported model. Finally, several models incorporated environmental data as a linear predictor of movement rates. The addition of the environmental variables, in order of importance, river width to depth ratio, river flow, water turbidity, river flow to mean river flow ratio, and water velocity all resulted in improved model fit. Water temperature did not improve model fit. These environmental associations are discussed and potential improvements on the travel time model are suggested.
引用
收藏
页码:257 / 271
页数:15
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