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Spatial synchrony in the response of a long range migratory species (Salmo salar) to climate change in the North Atlantic Ocean
Authors:Maxime Olmos  Mark R Payne  Marie Nevoux  Etienne Prvost  Grald Chaput  Hubert Du Pontavice  Jrme Guitton  Timothy Sheehan  Katherine Mills  Etienne Rivot
Institution:Maxime Olmos,Mark R. Payne,Marie Nevoux,Etienne Prévost,Gérald Chaput,Hubert Du Pontavice,Jérôme Guitton,Timothy Sheehan,Katherine Mills,Etienne Rivot
Abstract:A major challenge in understanding the response of populations to climate change is to separate the effects of local drivers acting independently on specific populations, from the effects of global drivers that impact multiple populations simultaneously and thereby synchronize their dynamics. We investigated the environmental drivers and the demographic mechanisms of the widespread decline in marine survival rates of Atlantic salmon (Salmo salar) over the last four decades. We developed a hierarchical Bayesian life cycle model to quantify the spatial synchrony in the marine survival of 13 large groups of populations (called stock units, SU) from two continental stock groups (CSG) in North America (NA) and Southern Europe (SE) over the period 1971–2014. We found strong coherence in the temporal variation in postsmolt marine survival among the 13 SU of NA and SE. A common North Atlantic trend explains 37% of the temporal variability of the survivals for the 13 SU and declines by a factor of 1.8 over the 1971–2014 time series. Synchrony in survival trends is stronger between SU within each CSG. The common trends at the scale of NA and SE capture 60% and 42% of the total variance of temporal variations, respectively. Temporal variations of the postsmolt survival are best explained by the temporal variations of sea surface temperature (SST, negative correlation) and net primary production indices (PP, positive correlation) encountered by salmon in common domains during their marine migration. Specifically, in the Labrador Sea/Grand Banks for populations from NA, 26% and 24% of variance is captured by SST and PP, respectively and in the Norwegian Sea for populations from SE, 21% and 12% of variance is captured by SST and PP, respectively. The findings support the hypothesis of a response of salmon populations to large climate‐induced changes in the North Atlantic simultaneously impacting populations from distant continental habitats.
Keywords:Atlantic salmon  bottom‐up  climate change  environmentally driven changes  hierarchical Bayesian model  marine survival  spatial covariation  stage‐based life cycle model
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