Using restoration monitoring data to inform an H-integrated Chinook salmon recovery strategy
Estuarine and nearshore habitats are critical to sustainable fisheries management. While habitat conservation and restoration measures have been implemented in Puget Sound and beyond, there is still a need to examine restoration actions alongside other management efforts to determine whether river delta systems can be managed synergistically. This includes integrated assessments that account for factors implicated in salmon decline, often referred to as the “four Hs:” habitat, hatcheries, harvest, and, if relevant, hydropower.
Building upon science and management lessons learned from throughout Puget Sound, a scalable H-Integrated approach may help maximize the efficiency and effectiveness of ongoing and future capital restoration projects with the potential for policy impacts at the local, state, and federal levels.
Project Objectives
The goal of this project is to develop a scalable and dynamic H-Integrated framework for restoration planning that incorporates all four “Hs” of salmon decline: habitat loss, hydropower, hatchery production, and harvest.
This approach is intended to help managers identify restoration actions that are most likely to mitigate negative interactions between different species and stocks of salmon, increase fishing opportunities, and maintain habitat function in the face of climate change and shifts in hydropower-limited connectivity. This H-Integration framework will be scalable and dynamic, allowing managers to account for current population needs and projected shifts due to hatchery supplementation, harvest rates, marine survival, improved fish passage, and climate change. We expect that this framework will aid in the implementation of restoration actions meant to improve the integrity and resilience of ecosystem processes, while also promoting sound decision making that transcends limited, habitat-centric restoration approaches.
The utility of H-Integrated approaches for restoration planning and salmon recovery has been recognized for several decades, yet they remain underutilized due to a lack of transparent guidelines and uncertainties surrounding data needs and limitations. H-Integration is commonly implemented using life cycle or stock-recruitment type population models, where habitat, hatchery, and harvest indicators are adjusted to determine their effects on population trajectories. Although such models are generally quite flexible, there is no “one-size-fits-all” approach. An optimal H-Integration framework would be fully scalable and dynamic—that is, it accounts for the complexity of available data inputs and methods and can be adapted to meet the needs of restoration managers.
Objective 1: Derive spatially explicit carrying capacity estimates for the Nisqually River Delta to inform wild Chinook salmon recovery goals and hatchery management strategies.
Restoration modifies the availability, configuration, and quality of estuarine habitats. It is therefore vital to assess how previous and planned restoration actions affect the capacity of a system to support juvenile salmon and other estuary-dependent fishes. This includes determining whether restoring habitat has/will mitigate potentially negative interactions between wild and hatchery salmon and competition among species.
To satisfy Objective 1, we will use an existing spatially explicit bioenergetics model to derive carrying capacity estimates for the Nisqually River Delta. Estimates will be derived for the following scenarios:
- Before and after large scale restoration efforts in 2009
- Present day, moderate, and high rates of sea-level rise
- Rising air temperatures based on IPCC predictions
- Additional inputs of suspended sediments (hydropower management)
- Increased connectivity with areas south of I-5 resultant from a proposed transportation improvement/restoration project
By integrating climate change and management (Habitat/Hydropower) scenarios with the Tribe’s wild Chinook salmon recovery goals and potential Hatchery management strategies, we hope to determine how hatchery production can be modified to minimize stress on the wild salmon population. We aim to scale up existing carrying capacity estimates by accounting for the prey needs of multiple estuarine fish species and by using an individual-based bioenergetics modeling approach. Carrying capacity estimates may be simplified by using temperature-only bioenergetics models and/or habitat-specific prey availability estimates based on established literature values.
Objective 2: Use an H-Integrated Population Model (H-IPM) to estimate Chinook salmon survival rates and the duration of the Tribal fishing season under restoration, management, and climate change scenarios.
Integrated population models (IPM) are quantitative tools that can be used to predict salmon survival and productivity. These models are ideal for describing stochastic population dynamics and can be used in systems with noisy or incomplete data. They rely on stock-recruitment datasets and take the form of commonly used density dependent population models (e.g., Ricker, Beverton-Holt). In most instances, Bayesian inference is used to estimate model parameters.
For Objective 2, we will develop an H-Integrated IPM (H-IPM) that accounts for the demographic characteristics of the Nisqually fall Chinook salmon population, the relationship between early marine growth and survival (informed by carrying capacity estimates in Objective 1), environmental conditions, hatchery production, and harvest rates. Not only will this allow us to directly quantify the relationship between habitat restoration, estuarine growth, and survival, but it will allow us to estimate the duration of the Tribal fishing season or “time spent on the water”—a metric of population success that the Nisqually Indian Tribe has identified as their priority. We will run the model for the climate, restoration, and management scenarios listed in Objective 1, and will also test the effect of variable fitness between hatchery and wild spawners and shifts in marine, estuarine, and freshwater conditions under climate change.
Objective 3: Develop a resource guide for restoration practitioners in Puget Sound outlining best practices for using H-Integration as a decision support tool for restoration planning.
For Objective 3, we intend to share lessons learned from the Nisqually River Delta with other systems throughout Puget Sound. We will develop a freely available resource guide outlining data inputs, analytical tools, and key uncertainties for using H-Integration as a decision support tool to increase the efficiency and effectiveness of restoration planning and salmon management. This guide will highlight modular and scalable alternatives to the analytical products outlined in Objectives 1 and 2. We will conduct a sensitivity (i.e., “scalability”) analysis of our H-IPM whereby the quality and quantity of data and the complexity of the analytical inputs will be incrementally reduced, and the relative accuracy of the model will be assessed. This can inform restoration monitoring programs by identifying minimum and optimal data requirements to provide the greatest added-value for H-Integrated and other analytical approaches. Additionally, we will hold two synthesis workshops—one toward the beginning of the project and a follow-up workshop at the end—which will inform the content of the resource guide and the ways in which lessons learned are shared with potential users. In preparation for compiling the resource guide and planning the synthesis workshops, we will form an advisory committee that includes science and policy experts from throughout Puget Sound. The advisory committee will play a crucial role in shaping how open access deliverables from Objectives 1, 2, and 3 are communicated with the public and with interested stakeholders.
Project Leads and Partners
- Melanie Davis (USGS, Oregon Cooperative Fish and Wildlife Research Unit), Isa Woo, and Susan De La Cruz (USGS, Western Ecological Research Center) are in charge of project administration and overseeing the use of Nisqually “habitat” data
- Bryan Reiley (Oregon State University) will synthesize data, develop IPM models, and lead workshops
- Chris Ellings, Sayre Hodgson, Craig Smith, and David Troutt (Nisqually Indian Tribe, Department of Natural Resources) are serving in an advisory capacity on behalf of the Tribe, and are overseeing the use of “harvest” and “hatchery” data
