DOI: 10.7291/d19975
title: California steelhead abundance and environmental conditions timeseries

description: Weather extremes, such as drought, are predicted to be a strong
 determinant of species persistence under climate change. Yet predictions
 often fail to consider that variation in streamflow responses, variation
 in population dynamics, or adaptations to drought could buffer species
 against extremes. In this study we examined the responses of eight
 California (USA) steelhead populations to a severe drought from 2012 to
 2016. We observed that streamflows were highly synchronous across the
 region in all seasons and did not appear to buffer drought impacts.
 Population dynamics were variable across the region and did appear to
 buffer the region from drought impacts. Some populations had very low
 productivity for four years associated with the drought, while others had
 slightly below-average productivity for only two years. Population
 synchrony was associated with spring-smolt flow, temperature and drought
 over time, but was not associated with winter-spawner or summer-juvenile
 conditions, suggesting populations may be adapted to drought. Our results
 highlight how regional buffering and adaptation can be important
 mechanisms against climate extremes both now and into the future.
description: Data were collected from a variety of sources. See Ohms et al.
 2024 for data source details.
description: # California steelhead abundance and environmental covariates
 [https://doi.org/10.7291/D19975](https://doi.org/10.7291/D19975) **The
 data is contained in two .xlsx files: EnvironmenalCovariates.xlsx and
 SpawnerCounts.xlsx.** EnvironmenalCovariates.xlsx contains all of the
 environmental covariate data we used in the analysis. All parameters,
 units, and original data sources are described in Ohms et al. 2024. There
 are no missing data in this file. NA values in the month field for
 "pinksalmon_Asia"*, "*pinksalmon_NorthPacific" and
 "pinksalmon_NorthAmerica" are present because these are annual
 data that are not associated with a month. SpawnerCounts.csv contains the
 estimated number of spawners in a given population by year. Years with
 missing data are excluded from the dataset. **SpawnerCounts.xlsx**
 ***Fields***: Year, Total, PopName, CountType Year: the primary year in
 which fish returned (i.e., were counted). For example, fish returning in
 winter 2018/2019 have a year assignment of 2019.   Total: the abundance of
 spawners estimated in that year (extrapolated from counts). PopName:
 population where spawners estimated CountType: methods used for counting
 and estimating spawners **EnvironmentalCovariates.xlsx** ***Fields***:
 Year, Month, Covariate, Value Year: the year during which the parameter
 values were measured Month: the month during which the parameter values
 were measured Covariate: environmental covariate measured Value: the value
 of the parameter. Units are as follows:  * pink salmon (Asia, North
 Pacific, and North America): abundance (wild+hatchery) in millions of fish
 * habitat compression index: standardized index for amount of cool water
 (&lt;12 degrees C) at 2-m depth adjacent to the coastline. Details at
 Santora et al. 2020
 ([https://doi.org/10.1038/s41467-019-14215-w](https://doi.org/10.1038/s41467-019-14215-w)) * krill: catch-per-unit-effort of coastal shelf krill (Sakuma et al. 2016. CalCOFI Rep., Vol. 57) * thermal marine habitat: mean km^2 between 5-15 degrees C across steelhead ocean distribution * rockfish: catch-per-unit-effort of coastal young-of-year rockfish (Sakuma et al. 2016. CalCOFI Rep., Vol. 57) * air temperature (temperate forest and Mediterranean Forest): mean monthly temperature, degrees C * stream flow (Carmel, Eel, Little, Noyo, Soquel, CasparNF): mean monthly streamflow, cubic feet per second