Redd and carcass data are made available courtesy of the California Department of Fish and Wildlife (CDFW). The data are provisional and subsequent review may result in revisions to the data. The data were not collected following a study design for various egg growth and survival models. It is important to consider data limitations when used in modeling applications. For example, the aerial redd dataset is limited due to its susceptibility to turbid water and other environmental characteristics that can make viewing the redd locations difficult.
The CDFW makes no claims, promises, or guarantees about the accuracy, completeness, reliability, adequacy of these data and expressly disclaims liability for errors and omissions in these data. No warranty of any kind, implied, limited to the warranties of non-infringement of third party rights, title merchantability, fitness for a particular purpose, and freedom from computer virus, is given with respect to these data.
Smoothing is applied to allocate the redds or carcasses more realistically in time. The true timing of these events can be lost because redds and carcasses are surveyed intermittently. The smoothing process distributes any non-zero count of redds on a particular day back in time uniformly to the previous non-zero count day. The first day with non-zero counts is distributed back in time uniformly across 6 days.
Under specific user selections for Fish Model: Spawning to Migration, the program includes the CV-TEMP model output for predicted Daily Average Temperature. For more information, please refer to Central Valley Temperature Mapping and Prediction (CVTEMP).
When temperature data are un-available for specific days, a 10-year average is used to supply the missing values.
Multiple temperature-dependent mortality model options are available: exponential models (e.g., Water Forum 2020, Zeug et al. 2012, SALMOD 2006), linear models (e.g., Martin et al. 2017, Anderson et al. 2022), a Weibull-type model, constant survival, and no temperature-dependent mortality (or null model). The USGS 2018 Threshold model is no longer available on the SacPAS Egg Growth Modeling webpage because it only applies to nuanced timeseries data (similar to Geist et al. 2006) where egg mortality occurs at, or near, fertilization only.
Egg development-rate modeling includes linear (Zeug et al. 2012), mechanistic (Beer and Anderson 1997), empirical (Jensen et al. 1999), and power-law (Beacham and Murray 1990, USGS 2018) models.
Anderson, J. 2018. Using river temperature to optimize fish incubation metabolism and survival: a case for mechanistic models. bioRxiv. DOI 10.1101/257154. Available 9 March 2018 from: https://www.biorxiv.org/content/early/2018/02/05/257154
Anderson, J., W.N. Beer, J.A. Israel, S. Greene. 2022. Targeting river operations to the critical thermal window of fish incubation: Model and case study on Sacramento River winter-run Chinook salmon. River Research and Applications 38950: 895-905. DOI:10.1002/rra.3965
Beacham, T.D. and C.B. Murray. 1990. Temperature, egg size, and development of embryos and alevins of five species of Pacific salmon: A comparative analysis. Transactions of the American Fisheries Society. 119(6):927-945.
Beer, W.N., J. Anderson. 1997. Modelling the growth of salmonid embryos. Journal of Theoretical Biology. 189(3):297-306 DOI:10.1006/jtbi.1997.0515
Beer, W.N., and E.A. Steel. 2018. Impacts and implications of temperature variability on Chinook salmon egg development and emergence phenology Transactions of the American Fisheries Society. 147(1):3-15. DOI 10.1002/tafs.10025
Bartholow, J.M. and J. Heasley. 2006. Evaluation of Shasta Dam Scenarios Using a Salmon Production Model https://cbr.washington.edu/sacramento/fishmodel/BartholowHeasley2006.SALMOD.pdf
Bartholow, J.M. 2020. Modeling Chinook Salmon with SALMOD on the Sacramento River, California https://www.noaa.gov/sites/default/files/legacy/document/2020/Oct/07354626497.pdf
Bratovich, P., M. Neal, A. Ransom, P. Bedore, and M. Bryan. 2020. Chinook Salmon Early Lifestage Survival and Folsom Dam Power Bypass Considerations. Prepared for the Sacramento Area Water Forum. August 2020. Available from https://www.waterforum.org/wp-content/uploads/2020/09/Water-Forum-Water-Temp-Embryo-Survival-TM-9-23-20.pdf
CFS. 2010. A Revised Sacramento River Winter Chinook Salmon Juvenile Production Model. Cramer Fish Sciences. Available 9 May 2016 from: http://deltacouncil.ca.gov/sites/default/files/2014/11/November-2010-A-Revised-Sacramento-River-Winter-Chinook-Salmon-Juvenile-Production-Model.pdf
Dusek-Jennings, E., and A.N. Hendrix. 2020. Spawn Timing of Winter-Run Chinook in the Upper Sacramento River 18(2): https://doi.org/10.15447///sfews.2020v18iss2art5
Jager, H.I. 2011. Quantifying Temperature Effects on Fall Chinook Salmon https://info.ornl.gov/sites/publications/files/Pub33206.pdf
Jensen, J.O.T., M.E. Jensen. Aquaculture Assoc. of Canada S. A. N. B., Waddy S. 1999. IncubWin: A new Windows 95/98/NT computer program for predicting embryonic stages in Pacific salmon and steelhead trout Contributed Papers - Aquaculture Canada '99 Victoria BC, 28 pp.
Hance, D.J. et al. 2021, From drought to deluge: spatiotemporal variation in migration routing, survival, travel time and floodplain use of an endangered migratory fish. Can. J. Fish. Aquat. Sci. 00: 1-19 (0000) dx.doi.org/10.1139/cjfas-2021-0042
HCI. 1996 Hydrologic Consultants Inc. Chinook Salmon Mortality Model: Development, Evaluation, and Application as One Tool to Assess the Relative Effects of Alternative Flow and diversion Scenarios on the Lower American River (citation needed)
Martin, B., (four other authors). 2016. Modeling temperature dependent mortality of winter-run Sacramento River Chinook salmon. Available 20 June 2017 from: http://www.westcoast.fisheries.noaa.gov/publications/Central_Valley/Water%20Operations/nmfs_concurrence_on_the_bureau_of_reclamation_s_sacramento_river_temperature_management_plan-_june_28__2016.pdf
Martin, B.T., Pike, A., John, S.N., Hamda, N., Roberts, J., Lindley, S.T. and Danner, E.M. 2017. Phenomenological vs. biophysical models of thermal stress in aquatic eggs. Ecol Lett, 20: 50-59. https://doi.org/10.1111/ele.12705
NOAA/SWFSC Fisheries Ecology Division. 2017. RAFT Predicted Daily Average Temperature. (Temp_50) [Data file]. Available from http://oceanview.pfeg.noaa.gov/erddap/tabledap/cvtempLandscape.html
NOAA/NWFSC. Comprehensive Passage (COMPASS) Model - version 2.0 Available from www.cbr.washington.edu/sites/default/files/manuals/COMPASS_Manual_2019_Review_Draft_full.pdf
Oppenheim, B. 2014. Juvenile Production Estimate (JPE) Calculation and Use/Application of Survival Data from Acoustically-tagged Chinook Salmon Releases. Report prepared for the 2014 Annual Science Panel Review Workshop, November 6-7.
Perry, R.W. Eight authors. 2018. "STARS" Flow-mediated effects on travel time, routing, and survival of juvenile Chinook salmon in a spatially complex, tidally forced river delta. CJFAS 75(11):1886-1901. https://doi.org/10.1139/cjfas-2017-0310.
Pike, A., E. Danner, D. Boughton, F. Melton, R. Nemani, B. Rajagopalan, and S. Lindley. 2013. Forecasting river temperatures in real time using a stochastic dynamics approach. Water Resources Research 49(9):5168-5182. DOI: 10.1002/wrcr.20389
SALMOD 2006. See above: Bartholow and Heasley 2006.
Steel et al. Applying the mean free-path length model to juvenile Chinook salmon migrating in the Sacramento River, California. Environmental Biology of Fishes 103:1603-1617 DOI:10.1007/s10641-020-01046-8
Tillotson M.D., J. Hassrick, A.L. Collins, P. Corey. 2022. Machine Learning Forecasts to Reduce Risk of Entrainment Loss of Endangered Salmonids at Large-Scale Water Diversions in the Sacramento-San Joaquin Delta, California. San Francisco Estuary and Watershed Science. https://doi.org/10.15447/sfews.2022v20iss2art3
United States Bureau of Reclamation (USBR). 2008. Biological Assessment on the Continued Long-term Operations of the Central Valley Project and the State Water Project https://www.usbr.gov/mp/cvo/ocap_page.html
United States Fish and Wildlife (USFW). 2006. Relationships between flow fluctuations and redd dewatering and juvenile stranding for Chinook salmon and steelhead in the Sacramento River between Keswick Dam and Battle Creek. (PDF)
USFW. 2006. Upper Sacramento River winter Chinook salmon Carcass Survey Compendium Report, Return Years 2001-2005. https://www.fws.gov/redbluff/HE/Winter%20Chinook%20Carcass%20Survey/USFWS%202001%20-%202005%20Compendium%20Report.pdf
United States Geological Survey (USGS). 2018a. Application of the Stream Salmonid Simulator (S3) to the Restoration Reach of the Trinity River, California - Parameterization and Calibration. https://pubs.er.usgs.gov/publication/ofr20181174
USGS. 2018b. Model Structure of the Stream Salmonid Simulator (S3) A Dynamic Model for Simulating Growth, Movement, and Survival of Juvenile Salmonids https://pubs.er.usgs.gov/publication/ofr20181056
Water Forum 2020. See Bratovich et al. 2020.
Zeug S., P. Bergman, B. Cavallo, and K. Jones. 2012. Application of a Life Cycle Simulation Model to Evaluate Impacts of Water Management and Conservation Actions on an Endangered Population of Chinook Salmon. Environmental Modeling and Assessment. DOI 10.1007/s10666-012-9306-6.
SacPAS: Central Valley Prediction & Assessment of Salmon, University of Washington, Columbia Basin Research, www.cbr.washington.edu/sacramento/