Research about Pend Oreille River

USGS2019

Decision analysis for the reintroduction of Bull Trout into the lower Pend Oreille River, Washington

The decision to reintroduce a species can be difficult owing to conflicting opinions and objectives, as well as uncertainty of the outcome. Structured decision making addresses these considerations by identifying realistic fundamental objectives and building achievable management alternatives, within a quantitative modeling framework. The process is driven by participation of stakeholders that represent diverse objectives, policy mandates, and opinions regarding decision alternatives. We applied structured decision making to evaluate reintroduction of Bull Trout Salvelinus confluentus in the lower Pend Oreille River in northeastern Washington State. We engaged stakeholders from Tribal, municipal, county, state and federal agencies to specify fundamental objectives, formulate feasible reintroduction decisions, and conceptualize a modeling framework that includes biological information and stakeholder assumptions. Stakeholders requested iterative decision sets to determine the optimal recipient streams and release strategies. The optimal decision, based on the fundamental objective of maximizing adult abundance at year 10, was artificial propagation of 4500 juvenile Bull Trout coupled with translocation of 25 adult migrants to be reintroduced into a tributary and lake system that produced at least 18% more adult fish relative to alternatives. Sensitivity analyses were robust to the identity of the recipient stream (i.e., Sullivan Lake/Harvey Creek was always the optimal recipient stream) but suggested that maximizing the number of artificially produced juveniles released could produce a similar number of adult Bull Trout as the coupled release strategy. Results also suggested that ensuring fish passage at the Albeni Falls Dam in the mainstem Pend Oreille River could increase the abundance of adult fish. The process followed for this case study can be adapted to similar decisions regarding reintroduction or other translocations of fish in other systems.

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USGS2019

Simulating demography, genetics, and spatially explicit processes to inform reintroduction of a threatened char

The success of species reintroductions can depend on a combination of environmental, demographic, and genetic factors. Although the importance of these factors in the success of reintroductions is well‐accepted, they are typically evaluated independently, which can miss important interactions. For species that persist in metapopulations, movement through and interaction with the landscape is predicted to be a vital component of persistence. Simulation‐based approaches are a promising technique for evaluating the independent and combined effects of these factors on the outcome of various reintroduction and associated management actions. We report results from a simulation study of bull trout ( Salvelinus confluentus ) reintroduction to three watersheds of the Pend Oreille River system in northeastern Washington State, USA. We used an individual‐based, spatially explicit simulation model to evaluate how reintroduction strategies, life history variation, and riverscape structure (e.g., network topology) interact to influence the demographic and genetic characteristics of reintroduced bull trout populations in three watersheds. Simulation scenarios included a range of initial genetic stocks (informed by empirical bull trout genetic data), variation in migratory tendency and life history, and two landscape connectivity alternatives representing a connected network (isolation‐by‐distance) and a fragmented network (isolation‐by‐barrier, using the known existing barriers). A novel feature of these simulations was the ability to consider the interaction of both demographic and genetic (i.e., demogenetic) factors in riverscapes with implicit asymmetric movement probabilities across the barriers. We found that connectivity (presence or absence of barriers) had the largest effect on demographic and genetic outcomes over 200 yr, with a greater effect than both initial genetic diversity and life history variation. We also identified regions of the study system in which bull trout populations persisted across a wide range of demographic, life history, and environmental connectivity parameters. Finally, we found no evidence that initial neutral genetic diversity influenced genetic diversity and structure after 200 yr; instead, genetic drift due to stray rate and population isolation dominated and erased any initial differences in genetic diversity. Our results highlight the utility of spatially explicit demogenetic approaches in exploring and understanding population dynamics—and their implications for management strategies—in fresh waters.

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