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Temporal and Spatial Variation in Temperature and Oxygen at the Microscale: Key Niche Axes for Aquatic Life
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Abstract
To understand animal adaptations we need accurate estimates of the ecological factors impacting on organisms in nature. Whilst temperature is a well-established driver of physiological performance, its effects in aquatic systems are closely linked to water oxygenation. Oxygen levels are expected to differ spatially and fluctuate temporally much more strongly in water than on land, but our understanding of variation in temperature and oxygen levels in freshwaters remains limited. It is essential that environmental variation is recorded at spatial and temporal resolutions relevant to the organism. Here, we analyze spatial and temporal variation in water temperature and oxygenation across running and standing waters, using both microscale spot measurements and continuous loggers collecting data from the water column. Our results reaffirm that small-scale thermal gradients are much less pronounced in water than on land due to the high thermal conductivity and heat capacity of water. Regional weather conditions can therefore reliably predict water temperature across scales. By contrast, oxygen levels are much harder to predict from large-scale data as they can fluctuate sharply over very small spatial scales and within a single day, particularly in standing waters, exposing aquatic organisms to steep oxygen gradients. Our findings underscore the importance of incorporating fine-scale oxygen dynamics when studying aquatic species distributions and ecological strategies.
DOI
https://doi.org/10.32942/X2ZQ0J
Subjects
Life Sciences
Keywords
Aquatic ecology, biogeography, microclimate, modelling, climate change, downscaling, refugia, resolution, species distribution models, ponds, rivers, dissolved oxygen, hypoxia
Dates
Published: 2026-02-16 13:21
Last Updated: 2026-02-16 13:21
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
none
Data and Code Availability Statement:
Data and code are available at: https://doi.org/10.5281/zenodo.16927393
Language:
English
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