1 Nez Perce Tribe, Department of Fisheries Resources Management, P.O. Box 365, Lapwai, Idaho, 83540, USA

✉ Correspondence: Jay A. Hesse <>, Ryan N. Kinzer <>

Suggested Citation for Annual Results:
Hesse, J.A. and Kinzer, R.N., 2026. Snake River Anadromous Fish Status: Quasi-Extinction Threshold Analysis. Department of Fisheries Resources Management. Version: 14 May, 2026. Available: https://ryankinzer.github.io/SRAFS/

1 Quasi-Extinction Summary

Updates for the 2025 analysis:

  • Removed Little Salmon River from spring/summer Chinook Salmon analysis due to limited data from only a small portion of the population.
  • Included multiple time-series of observations for each population if available (i.e, spawning ground survey data, weir observations, PIT-tag based estimates)
  • Performed model selection on multiple candidate models with varying numbers of state processes, drift, process error, and observation error parameters
  • PIT-tag based estimates now include an expansion for available habitat not covered by the instream PIT-tag detection system (Ackerman et al. 2026, in prep)

1.1 Spring/summer Chinook Salmon

Natural-origin (wild) and hatchery-origin returns of Snake River spring/summer Chinook Salmon past Lower Granite Dam.

Figure 1.1: Natural-origin (wild) and hatchery-origin returns of Snake River spring/summer Chinook Salmon past Lower Granite Dam.

Table 1.1: The table provides summary counts of spring/summer Chinook salmon populations currently below minimum abundance thresholds, 50 spawners, and meeting the quasi-extinction threshold (4 consecutive years below 50 spawners), and the number of populations predicted to fall below 50 by return year 2030.
Metric All Snake River Populations Extant ESA-listed Populations
Populations 34 31
Below Minimum Abundance Threshold 32 (94%) 29 (94%)
Current Return Below 50 7 (21%) 7 (23%)
Currently Below Quasi-Extinction Threshold 3 (9%) 3 (10%)
Predicted Below 50 by 2030 8 (24%) 8 (26%)
Current status of natural-origin Snake River spring/summer Chinook Salmon relative to the quasi-extinction threshold (QET) and Columbia Basin Partnership goals.

Figure 1.2: Current status of natural-origin Snake River spring/summer Chinook Salmon relative to the quasi-extinction threshold (QET) and Columbia Basin Partnership goals.

Estimated slope parameters for natural-origin Snake River spring/summer Chinook Salmon abundance trends indicate an average annual growth rate of approximately 0% for the last 10-years, however, considerable variability exists across major population groups.

Figure 1.3: Estimated slope parameters for natural-origin Snake River spring/summer Chinook Salmon abundance trends indicate an average annual growth rate of approximately 0% for the last 10-years, however, considerable variability exists across major population groups.

1.2 Summer Steelhead

Natural-origin (wild) and hatchery-origin returns of Snake River summer steelhead past Lower Granite Dam.

Figure 1.4: Natural-origin (wild) and hatchery-origin returns of Snake River summer steelhead past Lower Granite Dam.

Table 1.2: The table provides summary counts of steelhead populations currently below minimum abundance thresholds, 50 spawners, and meeting the quasi-extinction threshold (4 consecutive years below 50 spawners), and the number of populations predicted to fall below 50 by return year 2030.
Metric All Snake River Populations Extant ESA-listed Populations
Populations 23 23
Below Minimum Abundance Threshold 18 (78%) 18 (78%)
Current Return Below 50 1 (4%) 1 (4%)
Currently Below Quasi-Extinction Threshold 1 (4%) 1 (4%)
Predicted Below 50 by 2030 2 (9%) 2 (9%)
Current status of natural-origin Snake River summer steelhead relative to the quasi-extinction threshold (QET) and Columbia Basin Partnership goals.

Figure 1.5: Current status of natural-origin Snake River summer steelhead relative to the quasi-extinction threshold (QET) and Columbia Basin Partnership goals.

Modeled abundance trends of natural-origin Snake River summer steelhead indicate an annual 3% decline for the last 10-years.

Figure 1.6: Modeled abundance trends of natural-origin Snake River summer steelhead indicate an annual 3% decline for the last 10-years.

2 Methods

2.1 Datasets

  1. NOSAij: derived by co-managers and downloaded from Coordinated Assessments on 5/12/2026
    • Generally estimated from expanded redd counts or mark/recapture weir estimates
  2. Escapement: derived from PIT-tag observations and a branch occupancy model similar to Waterhouse et al. 2020
    • Includes a time-varying component to better describe run-timings of different populations passing Lower Granite Dam
    • Estimates have been expanded to the full population using available habitat models; see Ackerman et al. 2026 (in prep)

2.2 Data Analysis

2.2.1 Multivariate Auto-Regressive State-Space Model (MARSS; Holmes et al. 2012)

\[ \begin{aligned} \textbf{State process:} \quad & \mathbf{x}_{t} = \mathbf{x}_{t-1} + \mathbf{u} + \mathbf{w}_t, \quad \mathbf{w}_t \sim \mathcal{N}(0, \mathbf{Q}) \\ \\ \textbf{Observation process:} \quad & \mathbf{y}_{t} = \mathbf{Z}\mathbf{x}_{t} + \mathbf{a} + \mathbf{v}_t, \quad \mathbf{v}_t \sim \mathcal{N}(0, \mathbf{R}) \end{aligned} \]

where:

  • \(\mathbf{x}_t\): vector of latent (unobserved) state values at time \(t\)
  • \(\mathbf{u}\): vector of state-specific drift parameters representing mean temporal trends
  • \(\mathbf{w}_t\): process error vector with variance-covariance matrix \(\mathbf{Q}\)
  • \(\mathbf{y}_t\): vector of observed values at time \(t\)
  • \(\mathbf{Z}\): observation matrix linking latent states to observed time series
  • \(\mathbf{a}\): observation intercept or bias vector
  • \(\mathbf{v}_t\): observation error vector with variance-covariance matrix \(\mathbf{R}\)

The fitted MARSS models assumed a random-walk-with-drift state process where the autoregressive coefficient matrix was fixed as \(\mathbf{B} = \mathbf{I}\).

2.2.2 Fitted Models

2.2.2.1 State Structure (\(\mathbf{Z}\))

Models were fit assuming:

  • A single basin-wide latent process (1 state)
  • A latent process for each major population group:
    • 7 spring/summer Chinook salmon groups
    • 5 summer steelhead groups
  • A latent process for each population:
    • 34 spring/summer Chinook salmon populations
    • 22 summer steelhead populations

2.2.2.2 Drift Parameters (\(\mathbf{u}\))

  • Equal drift across all state processes (1 parameter)
  • State-specific drift parameters (number of parameters equals the number of state processes)

2.2.2.3 Process Error Structure (\(\mathbf{Q}\))

  • Equal variance-covariance structure:
    • shared variance parameter
    • shared covariance parameter
  • Diagonal and equal variance:
    • equal variances across state processes
    • covariances fixed to zero
  • Diagonal and unequal variance:
    • unique variances for each state process
    • covariances fixed to zero

2.2.2.4 Observation Error Structure (\(\mathbf{R}\))

  • Diagonal and equal variance:
    • equal observation variances across time series
    • covariances fixed to zero
  • Diagonal and unequal variance:
    • unique observation variances for each time series
    • covariances fixed to zero

3 Results

3.1 Spring/summer Chinook Salmon

3.1.1 Observations

Table 3.1: Summary of abundance time-series used in modeling Snake River spring/summer Chinook Salmon populations (n = 52). Time-series length and data sources varied by population, with observations spanning across 15 return years; beginning in 2011 and ending in 2025. Abundance estimates were primarily based on spawning ground surveys and weir counts, with PIT-tag detections included for select populations. The 10th, 50th (median), and 90th percentiles of observed abundance values are provided to summarize distributional characteristics across years.
MPG Population Method Years # Years 10% 50% 90%
Dry Clearwater South Fork Clearwater River Upper Mainstem PIT-tag 2012-2025 13 145 270 746
Grande Ronde / Imnaha Big Sheep Creek PIT-tag 2011-2024 13 19 49 119
Catherine Creek SGS and Weir 2011-2025 15 45 145 473
PIT-tag 2011-2025 14 119 250 624
Grande Ronde River Upper Mainstem SGS and Weir 2011-2025 15 12 43 183
PIT-tag 2012-2025 11 34 103 160
Imnaha River Mainstem SGS and Weir 2011-2025 15 186 314 701
PIT-tag 2011-2025 14 224 490 1037
Lookingglass Creek PIT-tag 2011-2024 13 47 119 286
Minam River SGS and Weir 2011-2025 15 219 390 664
PIT-tag 2021-2025 5 293 336 491
Wallowa/Lostine Rivers SGS and Weir 2011-2024 14 197 491 1254
Wenaha River SGS and Weir 2011-2025 15 198 286 634
Lower Snake Asotin Creek SGS and Weir 2011-2016 6 1 4 26
PIT-tag 2011-2025 14 0 14 74
Tucannon River SGS and Weir 2011-2024 14 11 58 228
Middle Fork Salmon River Bear Valley Creek SGS and Weir 2011-2025 15 113 370 867
PIT-tag 2015-2024 8 102 332 744
Big Creek SGS and Weir 2011-2025 15 50 149 293
PIT-tag 2011-2025 14 225 582 1078
Camas Creek SGS and Weir 2011-2025 15 13 43 100
Chamberlain Creek SGS and Weir 2011-2025 14 35 216 521
Loon Creek SGS and Weir 2011-2025 15 10 38 100
Marsh Creek SGS and Weir 2011-2025 15 123 375 639
PIT-tag 2021-2025 5 190 411 558
Middle Fork Salmon River Lower Mainstem SGS and Weir 2011-2024 14 0 3 9
Middle Fork Salmon River Upper Mainstem SGS and Weir 2011-2025 15 26 57 126
Sulphur Creek SGS and Weir 2011-2025 15 12 43 150
South Fork Salmon River East Fork South Fork Salmon River SGS and Weir 2011-2018 8 287 562 832
PIT-tag 2011-2025 14 243 629 1079
Secesh River SGS and Weir 2011-2018 8 416 712 1086
PIT-tag 2011-2025 14 270 665 1173
South Fork Salmon River SGS and Weir 2011-2025 15 143 376 969
PIT-tag 2011-2025 14 447 1417 3985
Upper Salmon River East Fork Salmon River SGS and Weir 2011-2025 15 27 210 630
PIT-tag 2011-2017 6 122 398 534
Lemhi River SGS and Weir 2011-2025 15 95 208 502
PIT-tag 2011-2025 14 133 252 665
North Fork Salmon River SGS and Weir 2011-2025 15 8 54 172
PIT-tag 2016-2024 7 70 106 372
Pahsimeroi River SGS and Weir 2011-2025 15 75 133 401
PIT-tag 2011-2025 14 51 106 284
Panther Creek PIT-tag 2018-2025 7 95 186 289
Salmon River Lower Mainstem SGS and Weir 2011-2025 15 17 44 211
Salmon River Upper Mainstem SGS and Weir 2011-2025 15 122 326 642
PIT-tag 2011-2025 14 45 218 756
Valley Creek SGS and Weir 2011-2025 15 38 115 261
PIT-tag 2011-2025 14 87 199 484
Yankee Fork SGS and Weir 2011-2025 15 3 24 305
PIT-tag 2012-2025 13 34 44 270
Wet Clearwater Lochsa River PIT-tag 2017-2025 8 164 236 443
Lolo Creek PIT-tag 2012-2025 13 48 79 288

3.1.2 Model Fits

Table 3.2: Candidate models and number of parameters fit to spring/summer Chinook Salmon time-series observations to explain Snake River abundance trends.
Model Id Total Parameters Z U Q R logLik AICc \(\Delta\)AIC
23 108 mpg equal equalvarcov diagonal and unequal -449.21 1156.46 0.00
24 114 mpg unequal equalvarcov diagonal and unequal -444.69 1164.70 8.25
3 107 basin equal diagonal and equal diagonal and unequal -475.66 1206.51 50.06
15 107 mpg equal diagonal and equal diagonal and unequal -495.02 1245.23 88.78
19 113 mpg equal diagonal and unequal diagonal and unequal -490.33 1253.09 96.63
16 113 mpg unequal diagonal and equal diagonal and unequal -494.41 1261.24 104.79
36 141 pop unequal equalvarcov diagonal and unequal -453.33 1264.65 108.19
20 119 mpg unequal diagonal and unequal diagonal and unequal -489.84 1269.70 113.25
35 108 pop equal equalvarcov diagonal and unequal -508.94 1275.93 119.48
22 63 mpg unequal equalvarcov diagonal and equal -597.61 1334.55 178.10

3.1.3 State Process

Estimated abundance (natural-log) trends for the seven state processes (xtT) estimated from the best fitting Snake River spring/summer Chinook Salmon model (grey shading represents 95% CI's). The blue line indicates the MARSS drift parameter and the estimated annual change in abundance across the 15 years of observations.

Figure 3.1: Estimated abundance (natural-log) trends for the seven state processes (xtT) estimated from the best fitting Snake River spring/summer Chinook Salmon model (grey shading represents 95% CI’s). The blue line indicates the MARSS drift parameter and the estimated annual change in abundance across the 15 years of observations.

3.1.4 Modeled Observations

Empirical natural-origin abundance estimates for Snake River spring/summer Chinook Salmon (points) and estimated population trends (ytT) from the best fitting model (line).

Figure 3.2: Empirical natural-origin abundance estimates for Snake River spring/summer Chinook Salmon (points) and estimated population trends (ytT) from the best fitting model (line).

3.1.5 5-Year Predictions

Estimated and predicted population abundance trends for natural-origin Snake River Chinook Salmon. Red points and triangles indicated an estimated annual return of 50 or fewer spawners.

Figure 3.3: Estimated and predicted population abundance trends for natural-origin Snake River Chinook Salmon. Red points and triangles indicated an estimated annual return of 50 or fewer spawners.

3.2 Summer Steelhead

3.2.1 Observations

Table 3.3: Summary of abundance time-series used in modeling Snake River summer steelhead populations (n = 27). Time-series length and data sources varied by population, with observations spanning across 15 return years; beginning in 2011 and ending in 2025. Abundance estimates were primarily based on PIT-tag detections, with spawning ground surveys and weir counts included for select populations. The 10th, 50th (median), and 90th percentiles of observed abundance values are provided to summarize distributional characteristics across years.
MPG Population Method Years # Years 10% 50% 90%
Clearwater River Clearwater River Lower Mainstem SGS and Weir 2011-2025 15 383 1138 3607
PIT-tag 2011-2025 15 937 1526 2926
Lochsa River PIT-tag 2017-2025 9 308 480 1290
Lolo Creek PIT-tag 2012-2025 14 123 214 648
Selway River PIT-tag 2017-2025 9 243 511 805
South Fork Clearwater River PIT-tag 2012-2025 14 132 419 1023
Grande Ronde River Grande Ronde River Lower Mainstem PIT-tag 2019-2023 5 1023 1523 1703
Grande Ronde River Upper Mainstem SGS and Weir 2011-2018 8 1180 2528 3754
PIT-tag 2013-2025 13 390 575 1398
Joseph Creek SGS and Weir 2011-2017 7 1461 2149 4008
PIT-tag 2011-2025 15 386 738 2028
Wallowa River PIT-tag 2014-2025 12 397 572 1029
Imnaha River Imnaha River PIT-tag 2011-2025 15 686 1452 2849
Lower Snake Asotin Creek PIT-tag 2011-2025 15 432 707 2535
Tucannon River PIT-tag 2011-2025 15 350 560 1125
Salmon River East Fork Salmon River PIT-tag 2012-2019 5 40 81 123
Lemhi River PIT-tag 2011-2025 15 49 105 399
Little Salmon River SGS and Weir 2011-2025 15 153 399 1756
PIT-tag 2013-2025 11 50 133 331
Middle Fork Salmon River Lower Mainstem PIT-tag 2011-2025 15 198 663 1315
Middle Fork Salmon River Upper Mainstem PIT-tag 2020-2025 6 104 170 266
North Fork Salmon River PIT-tag 2019-2025 6 69 138 174
Pahsimeroi River PIT-tag 2011-2025 14 10 35 149
Panther Creek PIT-tag 2018-2025 8 240 331 509
Salmon River Upper Mainstem PIT-tag 2011-2025 15 73 217 795
Secesh River PIT-tag 2011-2025 15 27 57 237
South Fork Salmon River PIT-tag 2011-2025 15 200 576 1809

3.2.2 Model Fits

Table 3.4: Candidate models and number of parameters fit to summer steelhead time-series observations to explain Snake River abundance trends.
Model Id Total Parameters Z U Q R logLik AICc \(\Delta\)AIC
2 57 basin equal equalvarcov diagonal and unequal -169.6225 478.3856 0.000000
13 58 mpg equal equalvarcov diagonal and unequal -169.7832 481.6886 3.302969
25 58 pop equal equalvarcov diagonal and unequal -171.0160 484.1541 5.768484
14 62 mpg unequal equalvarcov diagonal and unequal -170.6061 495.4912 17.105616
26 80 pop unequal equalvarcov diagonal and unequal -149.6921 513.3841 34.998549
1 31 basin equal equalvarcov diagonal and equal -226.2907 521.4466 43.060960
11 32 mpg equal equalvarcov diagonal and equal -226.3920 524.1174 45.731811
23 32 pop equal equalvarcov diagonal and equal -226.7806 524.8945 46.508947
12 36 mpg unequal equalvarcov diagonal and equal -225.4840 532.3482 53.962649
24 54 pop unequal equalvarcov diagonal and equal -203.4792 537.2893 58.903714

3.2.3 State Process

Estimated abundance (natural-log) trend for a single state process (xtT) as estimated from the best fitting Snake River summer steelhed model (grey shading represents 95% CI's). The blue line indicates the MARSS drift parameter and the estimated annual change in abundance across the 15 years of observations.

Figure 3.4: Estimated abundance (natural-log) trend for a single state process (xtT) as estimated from the best fitting Snake River summer steelhed model (grey shading represents 95% CI’s). The blue line indicates the MARSS drift parameter and the estimated annual change in abundance across the 15 years of observations.

3.2.4 Modeled Observations

Empirical natural-origin abundance estimates for Snake River summer steelhead (points) and estimated population trends (ytT) from the best fitting model (line).

Figure 3.5: Empirical natural-origin abundance estimates for Snake River summer steelhead (points) and estimated population trends (ytT) from the best fitting model (line).

3.2.5 5-Year Predictions

Estimated and predicted population abundance trends for natural-origin Snake River summer steelhead. Red points and triangles indicated an estimated annual return of 50 or fewer spawners.

Figure 3.6: Estimated and predicted population abundance trends for natural-origin Snake River summer steelhead. Red points and triangles indicated an estimated annual return of 50 or fewer spawners.

4 Version Archive

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