SummaryPredicting when, where and with what magnitude climate change is likely to affect the fitness, abundance and distribution of organisms and the functioning of ecosystems has emerged as a high priority for scientists and resource managers. However, even in cases where we have detailed knowledge of current species' range boundaries, we often do not understand what, if any, aspects of weather and climate act to set these limits. This shortcoming significantly curtails our capacity to predict potential future range shifts in response to climate change, especially since the factors that set range boundaries under those novel conditions may be different from those that set limits today. We quantitatively examine a nine-year time series of temperature records relevant to the body temperatures of intertidal mussels as measured using biomimetic sensors. Specifically, we explore how a 'climatology' of body temperatures, as opposed to long-term records of habitat-level parameters such as air and water temperatures, can be used to extrapolate meaningful spatial and temporal patterns of physiological stress. Using different metrics that correspond to various aspects of physiological stress (seasonal means, cumulative temperature and the return time of extremes) we show that these potential environmental stressors do not always occur in synchrony with one another. Our analysis also shows that patterns of animal temperature are not well correlated with simple, commonly used metrics such as air temperature. Detailed physiological studies can provide guidance to predicting the effects of global climate change on natural ecosystems but only if we concomitantly record, archive and model environmental signals at appropriate scales.
Diel vertical migrations (DVM) of zooplankton and micronekton are observed throughout the world ocean, where they influence ecological interactions and biogeochemical cycles. Despite their common occurrence, descriptions of the characteristics of these migrations are currently limited at the large scale. We analyze trajectories of migrations from a global dataset of acoustic backscatter to identify the large‐scale patterns of the timing and speed of DVM. Sound scattering layers (SSL) leave the surface 21 ± 20 min before sunrise, and return to it 17 ± 23 min after sunset, while changes in bulk surface backscatter appear to be nearly synchronous to sunrise and sunset. Mean downward migrations (7.6 ± 3.6 cm s−1) are significantly faster than mean upward migrations (6.5 ± 3.5 cm s−1). Furthermore, coherent and predictable variations of migration properties at the scale of ocean basins are evident. These variations appear to be related to the depths of migration, such that deeper migrations, observed for example in the subtropical gyres, the western tropical Pacific and the Southern Ocean, show earlier departures and later arrivals than shallower migrations. Vertical velocities peak in the tropical and subtropical regions, and decline towards the poles, with the strongest declines observed in the North Pacific. Migration velocities are also correlated to migration depths, with deeper migrations being faster than shallow migrations. These new constraints on the characteristics of migrating SSL could help shed light on the physiological, ecological, and environmental controls that regulate DVM behavior.
At a proximal level, the physiological impacts of global climate change on ectothermic organisms are manifest as changes in body temperatures. Especially for plants and animals exposed to direct solar radiation, body temperatures can be substantially different from air temperatures. We deployed biomimetic sensors that approximate the thermal characteristics of intertidal mussels at 71 sites worldwide, from 1998-present. Loggers recorded temperatures at 10–30 min intervals nearly continuously at multiple intertidal elevations. Comparisons against direct measurements of mussel tissue temperature indicated errors of ~2.0–2.5 °C, during daily fluctuations that often exceeded 15°–20 °C. Geographic patterns in thermal stress based on biomimetic logger measurements were generally far more complex than anticipated based only on ‘habitat-level’ measurements of air or sea surface temperature. This unique data set provides an opportunity to link physiological measurements with spatially- and temporally-explicit field observations of body temperature.
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