Disentangling risks to an endangered fish: using a state-space life cycle model to separate natural mortality from anthropogenic losses

Abstract

State-space population models are becoming a common tool to guide natural resource management, because they address the statistical challenges arising from high observation error and process variation while improving inference by integrating multiple, disparate datasets. A hierarchical state-space life cycle model was developed, motivated by delta smelt (Hypomesus transpacificus), an estuarine fish experiencing simultaneous risks of entrainment mortality from out-of-basin water export and natural mortality. Notable model features included a covariate-dependent instantaneous rates formulation of survival, allowing estimation of multiple sources of mortality, and inclusion of relative observation bias parameters, allowing integration of differently scaled abundance indices and entrainment estimates. Simulation testing confirmed that two sources of mortality, process variation, and data integration parameters could be estimated. Delta smelt entrainment mortality was associated with environmental conditions used to manage entrainment, and recruitment and natural mortality were related to temperature, outflow, food, and predators. Although entrainment mortality was reduced in recent years, ecosystem conditions did not appear to support robust spawning or over-summer survival of new recruits, manifesting as a 98% reduction of adults during 1995-2015.

Combining multiple data sources with different biases in state‐space models for population dynamics

“…We will refer to the $$$ {\beta}_{\cdot, 0} $$$ as “intercept” parameters and $$$ {\beta}_{\cdot, 1},{\beta}_{\cdot, 2},\dots $$$ as “slope” parameters, even though on the untransformed scale the vital rate curves are not linear. Alternative formulations for how $$$ {\rho}_t $$$ and $$$ {\phi}_{i,t} $$$ are represented for this type of model were given by Maunder and Deriso (2011) and Smith et al (2021). The quantity $$$ {N}_{n,0} $$$ may be treated as a parameter.…”

Identifying minimum freshwater habitat conditions for an endangered fish using life cycle analysis

“…Recent population modeling by Kimmerer and Rose (2018) and Smith et al (2021) has provided some direct quantitative insight into Delta Smelt population growth rates by comparing changes in growth rates between a limited set of scenarios reflecting different habitat conditions. The former study focused on the relative influence of food availability versus entrainment throughout the affected parts of the life cycle.…”

A bioenergetics‐based index of habitat suitability: Spatial dynamics of foraging constraints and food limitation for a rare estuarine fish

“…Nonetheless, several lines of evidence suggest a role of food limitation in the population dynamics of Delta Smelt. Mean fork length declined for a number of years shortly after the overbite clam invasion (Bennett 2005); adult mortality is correlated with prey abundance (Mac Nally et al 2010; Maunder and Deriso 2011; Smith et al 2021), and histopathologic assessments have shown evidence for frequent depletion of liver glycogen reserves (Hammock et al 2015; Teh et al 2020). Delta Smelt food limitation may be particularly acute in the summer, when water temperatures often reach physiologically stressful levels (Komoroske et al 2016) and the seasonal maximum of overbite clam grazing limits accumulation of plankton in the upper estuary (Kimmerer and Thompson 2014; Kimmerer et al 2019).…”