Geology topics

Neala W. Kendall

Publications and source records attributed to Neala W. Kendall.

3 recordsLinked to original sources

USGS2025

Declining marine survival of steelhead trout linked to climate and ecosystem change

Species with complex life cycles, such as anadromous fish that perform spawning migrations between freshwater and the ocean, may be particularly sensitive to global change because freshwater and marine habitats experience distinct shifts in climate and ecosystem dynamics. Abundances of wild steelhead trout ( Oncorhynchus mykiss ) have declined across most of their range over the past 40–50 years. We examined whether declines in steelhead survival can be linked to changing climate conditions and species interactions. A novel hierarchical integrated population model that accounts for the species' complex life history was fitted to data from multiple wild steelhead populations on the Washington coast, U.S.A. The model estimates recruitment residuals and kelt survival rates as time-varying processes, which reflect annual variation in survival before and after first maturation. We found that survival rates of immature steelhead (recruits) and adult steelhead (kelts) have declined over time and that survival trends across populations were strongly associated with climate and ecosystem change, specifically summer sea surface temperature and pink salmon abundance in the North Pacific Ocean, the NPGO index and river flows. Including these drivers in the model reduced unexplained annual variation in shared recruitment and kelt survival anomalies and largely accounted for their negative long-term trends. Our findings provide evidence that rising temperatures and increased interspecific competition at sea have contributed to declines in steelhead survival over the last five decades. Considering projected warming and high pink salmon abundances in the ocean, steelhead will likely continue to experience low marine survival rates.

Washington↗

USGS2022

Life-cycle model reveals sensitive life stages and evaluates recovery options for a dwindling Pacific salmon population

Population models, using empirical survival rates estimates for different life stages, can help managers explore whether various management options could stabilize a declining population or restore it to former levels of abundance. Here we used two decades of data on five life stages of the Cedar River, USA Sockeye Salmon, Oncorhynchus nerka , population to create and parameterize a life-cycle model. This formerly large but unproductive population is now in steep decline, despite hatchery enhancement. We gathered population-specific data on survival during five stages: 1) egg-to-fry, 2) fry-to-presmolt, 3) presmolt-to-adult return from the ocean, 4) adult en route from the ocean to the spawning grounds, and 5) reproduction. We ground-truthed the model to ensure its fit to the data, and then we modified survival and other parameters during various stages to examine future scenarios. Our analyses revealed that low survival of juveniles in Lake Washington (stage 2: averaging only 3% over the last 20 years), survival of adults returning to fresh water to spawn (stage 4), and survival of adults on spawning grounds to reproduce (stage 5) are likely limiting factors. Combined increases in these stages and others (specifically, the proportion of fish taken into the hatchery to be spawned) might also recover the population. As in other integrated hatchery populations, managers must weigh options relating to balancing the fraction of natural- and hatchery-origin fish, and our results showed that increasing the fraction of fish taken into the hatchery alone will not recover the population. Our model brings together population-specific data to help managers weigh conservation strategies and understand which stages and habitats are most limiting and how much survival must increase to achieve recovery targets. By extension, our analyses also reveal the utility of such models in other cases where stage-specific data are available.

North American Journal of Fisheries Management↗

USGS2021

Improving short-term recruitment forecasts for coho salmon using a spatiotemporal integrated population model

Fishery managers often rely on forecasts of future population abundance to set allowable harvest quotas or exploitation rates. While there has been substantial research devoted to identifying environmental factors that can predict recruitment for individual populations, such correlations often degrade over time, thereby limiting their utility for management. Conversely, examining multiple populations at once to detect shared, spatially structured patterns can offer insights into their recruitment dynamics that are advantageous for forecasting. Here, we develop a population dynamics model for natural origin coho salmon ( Oncorhynchus kisutch ) stocks in Washington State that leverages spatial and temporal autocorrelation in marine survival to improve one-year-ahead forecasts of adult returns. Executed in a Bayesian hierarchical integrated modelling framework, our spatiotemporal approach incorporates multiple data types and shares information among stocks to estimate key biological parameters that are informative for forecasting. Retrospective evaluation of one-year-ahead forecast skill indicated that the spatiotemporal integrated population model (ST-IPM) outperformed existing forecasts of Washington State coho salmon returns by 25–38 % on average. Moreover, the ST-IPM estimates parameters that were previously non-identifiable for many stocks, and propagates uncertainty from multiple contributing data sources into model forecasts. Our results add to a growing body of work demonstrating the utility of spatiotemporal and integrated approaches for modelling population dynamics, and the framework developed here has broad applications to the assessment and management of coho salmon in Washington State and elsewhere throughout their range.

Washington↗