An age structured model for assessment and management of Copper River chinook salmon

Thesis (M.S.) University of Alaska Fairbanks, 2001Chinook salmon in Alaska support human uses through a variety of fisheries. Age-structured assessment models are rarely used for estimating the abundance of exploited stocks. This thesis develops a model for the Copper River chinook salmon population to show its advantages over typical assessment models. Information consists of catch-age data from three fisheries (commercial, recreational, subsistence), and two sources of auxiliary data (escapement index, spawner-recruit relationship). Four approaches utilizing different information sources are explored. Results suggest that an approach utilizing pooled catch-age data with time-varying brood-year proportions produces the best estimates, although retrospective and sensitivity analyses suggest that all four approaches explored are robust. The model should assist managers when making management decisions, because it integrates all sources of information, accounts for uncertainty, and provides estimates of optimal escapement. The model shows promise as a method for assessing and forecasting chinook salmon populations

The role of density-dependent and –independent processes in spawning habitat selection by salmon in an Arctic riverscape

<div><p>Density-dependent (DD) and density-independent (DI) habitat selection is strongly linked to a species’ evolutionary history. Determining the relative importance of each is necessary because declining populations are not always the result of altered DI mechanisms but can often be the result of DD via a reduced carrying capacity. We developed spatially and temporally explicit models throughout the Chena River, Alaska to predict important DI mechanisms that influence Chinook salmon spawning success. We used resource-selection functions to predict suitable spawning habitat based on geomorphic characteristics, a semi-distributed water-and-energy balance hydrologic model to generate stream flow metrics, and modeled stream temperature as a function of climatic variables. Spawner counts were predicted throughout the core and periphery spawning sections of the Chena River from escapement estimates (DD) and DI variables. Additionally, we used isodar analysis to identify whether spawners actively defend spawning habitat or follow an ideal free distribution along the riverscape. Aerial counts were best explained by escapement and reference to the core or periphery, while no models with DI variables were supported in the candidate set. Furthermore, isodar plots indicated habitat selection was best explained by ideal free distributions, although there was strong evidence for active defense of core spawning habitat. Our results are surprising, given salmon commonly defend spawning resources, and are likely due to competition occurring at finer spatial scales than addressed in this study.</p></div

Map of the Chena River basin and its location in Alaska, USA (inset).

<p>The Core (C1 and C2) in the top panel represents the concentrated spawning area identified by aerial surveys and state biologists during carcass surveys, with the periphery (P1 and P2) located northeast of the core. The known distribution of spawning Chinook salmon in the Chena watershed is depicted by the Anadromous Waters Catalog (<a href="https://www.adfg.alaska.gov/sf/SARR/AWC/" target="_blank">https://www.adfg.alaska.gov/sf/SARR/AWC/</a>). The bottom panel shows predicted spawning habitat quality (range 0–1; darker is higher quality) based on resource selection function analysis for each study reach. The Middle Fork confluence is identified by MFC.</p

Model validation from assessment metrics.

<p>Model validation from assessment metrics.</p

Isodars for predicted counts between core and periphery Chinook salmon spawning areas in the Chena River, Alaska based on model 2 (see Table 1 for model list) count predictions.

<p>Individual gray lines represent the 10,000 isodars developed from bootstrapped counts from both a core and periphery habitat. The solid black line represents the mean isodar from the 10,000 simulated isodars. Isodars were constructed for the core and periphery, based on count predictions from each habitat of similar length (making the offset for each habitat the mean length of all study reaches).</p

Model validation from assessment metrics.

<p>Model validation from assessment metrics.</p

Conceptual models adapted from Morris [29] demonstrating the relationship between the fitness-density curve and isodar plots under density-dependent habitat selection.

<p>(A) Illustrates relative differences in fitness between the core and periphery and (C) the resulting isodar curve when habitat quality is not significantly different between habitats (slope = 1) under ideal free distributions (IFD). Panels (B) and (D) demonstrate relative differences in fitness between core and periphery and the resulting isodar curve when habitat quality is significantly different between habitats (slope ≠1) under IFD.</p

Predicted peak spawner counts from model 2 (y-axis; Table 1) as a function of annual Chinook salmon escapement estimates (1986–2013; x-axis) for the Chena River, Alaska.

<p>Observed (symbols) and predicted counts (lines and confidence ribbons) through time for C1 and P1 study reaches (top panel) and C2 and P2 study reaches (bottom panel) are shown. Dark and light grey ribbons represent 90% CIs for core and periphery habitats, respectively. Open symbols are observed counts used to fit the model and solid symbols are out-of-sample counts used for model validation. Predicted counts for each study reach are adjusted for the offset (study reach specific stream length).</p

Frequency distribution of slope and intercept estimates from the isodar model comparing counts in the core and periphery.

<p>Each vertical bar indicates the frequency of the coefficient estimate (slope or intercept) from the 10,000 isodar curves. Dark vertical lines indicate the critical value in which isodar coefficients (habitat quality different = slope, habitat quantity = intercept) would favor either the core or periphery. dark gray and light gray bands below vertical bars indicate the 90% and 95% confidence intervals, respectively.</p

Model selection results for candidate models predicting Chinook salmon peak spawner counts in the Chena River, Alaska.

<p>Model selection results for candidate models predicting Chinook salmon peak spawner counts in the Chena River, Alaska.</p