Quantifying thermal exposure for migratory riverine species: phenology of Chinook salmon populations predicts thermal stress

Migratory species are particularly vulnerable to climate change because habitat throughout their entire migration cycle must be suitable for the species to persist. For migratory species in rivers, predicting climate change impacts is especially difficult because there is a lack of spatially-continuous and seasonally-varying stream temperature data, habitat conditions can vary for an individual throughout its life cycle, and vulnerability can vary by life stage and season. To predict thermal impacts on migratory riverine populations, we first expanded a spatial stream network model to predict mean monthly temperature for 465,775 river km in the western U.S., and then applied simple yet plausible future stream-temperature change scenarios. We then joined stream temperature predictions to 44,396 spatial observations and life stage-specific phenology (timing) for 26 ecotypes (i.e. geographically distinct population groups expressing one of four distinct seasonal migration patterns) of Chin...

洄游物种（Migratory species）对气候变化尤为脆弱，因为其整个洄游周期内的所有栖息地均需满足适宜条件，物种方能存续。针对河流中的洄游物种，气候变化影响的预测难度尤甚，原因在于缺乏空间连续且随季节动态变化的溪流水温（stream temperature）数据，个体在整个生活史中其栖息地条件会发生变化，且物种的脆弱性会随生活史阶段与季节而异。为预测水温变化对洄游河流种群的影响，本研究首先扩展了空间溪流网络模型（spatial stream network model），以预测美国西部465775河道千米河段的月均水温；随后采用了简单但合理的未来溪流水温变化情景。随后，本研究将溪流水温预测结果与44396个空间观测点数据，以及26个生态型（ecotypes，即表现出四种独特季节性洄游模式之一的地理独立种群群）的特定生活史阶段物候（phenology，时间节律）数据进行匹配，相关数据涉及Chin...