California steelhead abundance and environmental conditions timeseries
Data files
Aug 06, 2024 version files 94.04 KB
Abstract
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.
README: California steelhead abundance and environmental covariates
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 (<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)
- 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
Methods
Data were collected from a variety of sources. See Ohms et al. 2024 for data source details.