Reply on RC1

Abstract

Spatiotemporally comprehensive stream temperature datasets are rare because interest in these data is relatively recent and there is little money to support instrumentation at regional or national scales. This lack of data has been recognized as a major limitation for understanding thermal regimes of riverine ecosystems. To overcome these barriers, we first aggregated one of the largest stream temperature databases on record with data from 1700 individual stations over nine years from 2009–2017 (n = 45,000,000 hourly measurements) across France (area = 552,000 km2). For each station, we calculated a simple, ecologically relevant metric–the thermal peak–that captures the magnitude of summer thermal extremes. We then used three statistical models to extrapolate the thermal peak to nearly every stream reach in France and Corsica (n = 105,800) and compared relative model performances among each other and with an air temperature proxy. In general, the hottest thermal peaks were found along major rivers, whereas the coldest thermal peaks were found along small rivers with forested riparian zones, strong groundwater inputs, and which were located in mountainous regions. Several key predictors of the thermal peak emerged, including drainage area, mean summer air temperature, minimum monthly specific discharge, and vegetation cover in the riparian zone. Despite differing predictor importance across model structures, we observed strong concordance among models in their spatial distributions of the thermal peak, suggesting its robustness as a useful metric at the subcontinental scale. However, air temperature was a poor proxy for the stream temperature thermal peak across nearly all stations and reaches, highlighting the growing need to measure and account for stream temperature in regional ecological studies.