{'fraction_non_alphanumeric': 0.022517321016166283, 'fraction_numerical': 0.005196304849884526, 'mean_word_length': 5.347985347985348, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Warming in the upper San Francisco Estuary: Patterns of water temperature change from five decades of data

Temperature is a key controlling variable from subcellular to ecosystem scales. Thus, climatic warming is expected to have broad impacts, especially in economically and ecologically valuable systems such as estuaries. The heavily managed upper San Francisco Estuary supplies water to millions of people and is home to fish species of high conservation, commercial, and recreational interest. Despite a long monitoring record (> 50 yr), we do not yet know how water temperatures have already changed or how trends vary spatially or seasonally. We fit generalized additive models on an integrated database of discrete water temperature observations to estimate long‐term trends with spatio‐seasonal variability. We found that water temperatures have increased 0.017°C yr−1 on average over the past 50 yr. Rates of temperature change have varied over time, but warming was predominant. Temperature increases were most widespread in the late‐fall to winter (November to February) and mid‐spring (April to June), coinciding with the winter development of juvenile Chinook salmon and spring spawning window of the endangered delta smelt. Warming was fastest in the northern regions, a key fish migration corridor with important tidal wetland habitat. However, no long‐term temperature trends were detected in October and were only observed in some regions in May, July, and August. These results can help identify optimal areas for restoration or refugia to buffer the effects of a warming climate, and the methods can be leveraged to understand the spatiotemporal variability in climate warming patterns in other aquatic systems.