Winter-run Chinook salmon resource selection function 2020

We use historic aerial redd surveys of Sacramento River winter-run Chinook salmon, coupled with 2D hydraulic modeling, and apply multivariable polynomial, logistic regression to calculate spawning resource selection functions (RSFs) based on water velocity and depth, and examine their interactions with water temperature. Our methods resulted in univariate and multivariate resource selection functions with interactions between both velocity and depth preference with changing temperature. Preferred depth increased and preferred velocity decreased with increasing temperature.

本研究采用萨克拉门托河冬季洄游奇努克鲑（Chinook salmon）的历史航拍产卵坑调查数据，结合二维水动力学模型（2D hydraulic modeling），运用多变量多项式回归与逻辑回归方法，基于水流速度与水深构建产卵资源选择函数（resource selection functions, RSFs），并探究其与水温的交互效应。本研究方法得到了同时考虑流速、水深偏好随水温变化的交互效应的单变量及多变量资源选择函数；随着水温升高，鲑鱼偏好的产卵水深逐渐增加，而偏好的水流速度则相应降低。