Modeling composite effects of marine and freshwater processes on migratory species

Abstract

Life histories of migratory species such as anadromous fishes make them particularly susceptible to composite effects of processes experienced across distinct habitats and life stages. Therefore, their population dynamics are difficult to quantify and manage without tools such as life‐cycle models. As a model species for which life‐cycle modeling is particularly useful, we provide an analysis of influential processes affecting dynamics of the Central Valley fall‐run Chinook salmon (CVFC) population (Oncorhynchus tshawytscha). This analysis demonstrates how, through identification of covariates that affect this population at each life stage and their relationship to one another, it is possible to identify actions that best promote sustainability for this anadromous species. We developed a life‐cycle model for CVFC examining primary processes influencing variability in observed patterns of escapement from 1988 to 2016. CVFC are a valuable fishery along the US West Coast; however, their natural population is a fraction of its historic size, and recent low escapements have resulted in substantial restrictions on the fishery. Our model explains 68.3% of variability in historic escapement values. The most influential processes include temperatures experienced during egg incubation, freshwater flow during juvenile outmigration, and environmentally mediated predation during early marine residence. This work demonstrates the need, and methodology, for considering the interactions between freshwater and marine dynamics when evaluating the efficacy of managerial practices in freshwater and the ocean, especially in the context of increased environmental variability, climate change, and dynamic predator populations. The methodology developed in this study can be used toward improved conservation and management of other anadromous fishes and migratory species.

Outmigration survival of wild Chinook salmon smolts through the Sacramento River during historic drought and high water conditions

“…Stream flow in rivers manipulated by agricultural practices can be a strong driver of smolt survival, as was documented on Idaho's Snake River where increased flows downstream of large dams resulted in higher survival rates for juvenile Chinook salmon migrating to the ocean (Connor et al 2003). In the Sacramento River, flow was found to be the top covariate in predicting outmigration survival of hatchery late-fall Chinook salmon, with years of high flow resulting in a three-fold increase in outmigration survival through the river (Henderson et al 2018;Friedman et al 2019). In addition to flow, higher water velocities can lead to improved smolt survival rates, likely because it promotes rapid downstream migration which reduces the exposure time to predators (Tiffan et al 2009).…”

A synthesis of the coast‐wide decline in survival of West Coast Chinook Salmon (Oncorhynchus tshawytscha,Salmonidae)

“…The reasons for poor marine survival of Chinook are likely multiple, with mechanisms proposed in the last decade alone including: growth (Claiborne et al., 2011; Duffy & Beauchamp, 2011; Graham et al., 2019; Howard, Murphy, Wilson, Moss, & Farley, 2016; Lewis et al., 2015; Losee et al., 2014; MacFarlane, 2010; Miller et al., 2014; Ohlberger et al., 2018; Orsi, 2013; Schindler et al., 2013; Tomaro et al., 2012); hatchery practices (Chamberlin et al., 2011; Nelson et al., 2019; Sabal et al., 2016; Tomaro, 2010); predation (Chasco et al., 2017; Friedman et al., 2019; Miller et al., 2013; Nelson et al., 2019; Seitz et al., 2019); competition (Cunningham et al., 2018; Miller et al., 2013); by‐catch mortality in fisheries (Cunningham et al., 2018); and ocean conditions (Dorner et al., 2017; Murphy et al., 2017; Ruff et al., 2017; Sharma et al., 2013).…”

Role of carryover effects in conservation of wild Pacific salmon migrating regulated rivers

“…They are often an assemblage of separate submodels with each one pertaining to one life stage or reach. The submodels allow for a more in-depth investigation within each life stage and the use of different types of data (Friedman et al 2019. However, we wanted to examine multiple life stages within an integrated model to standardize the magnitudes of association of covariates with survival.…”