Schmidt, A. E., L. W. Botsford, J. M. Eadie, R. W. Bradley, E. Di Lorenzo, J. Jahncke. 2014. Non-stationary seabird responses reveal shifting ENSO dynamics in the northeast Pacific. Mar Ecol Prog Ser 499: 249-258. DOI:10.3354/meps10629
Biological productivity in the North Pacific undergoes changes closely associated with large-scale climate phenomena such as El Niño-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) and the North Pacific Gyre Oscillation (NPGO). However, the relationships between biological and physical variables over time are not as simple as they seem. One such example is the relationship between seabird reproductive success and the shift in eastern Pacific El Niño to central Pacific El Niño events (Figure 1). To examine these complex dynamics, researchers studied common seabirds found along the central coast of California to determine if pelagic marine food webs respond to physical drivers the same way as they did in the past.
The authors collected 40 years of seabird ecology data from the Farallon Islands off central California to study the relationships between seabird reproductive success and environmental conditions. Two species of seabirds were examined, the Cassin’s auklet Ptycoramphus aleuticus and Brandt’s cormorant Phalacrococrax penicillatus (Figure 2). The authors chose these two species because they prey on animals at different levels in the food web. Cassin’s auklet feeds primarily on krill, while Brandt’s cormorant feeds on a variety of small, juvenile fish species like rockfish and anchovy. The annual reproductive successes of these birds are known to respond rapidly to the availability of their prey.
The authors look at correlations between seabird reproductive success and ocean conditions (Figure 3). This study defines reproductive success among seabirds as the mean number of chicks fledglings per breeding attempt. Ocean variables include sea surface temperature, sea level height and an index of cold, deep water upwelled to the surface (coastal upwelling). Seabird reproductive success was also correlated with Pacific variability such as ENSO, PDO and NPGO.
Relationships between reproductive success and ocean variables were highly variable. In the mid-1970s, reproductive success was greatest during La Niña conditions when coastal upwelling was enhanced along California and sea level height and sea surface temperatures were below normal (Figure 4). However, the effect of ENSO on seabirds off California may be weakening, while the effects of NPGO appear to increase.
Observed changes in seabird reproductive success suggest changes in the availability of prey lower in the food web. Food web structure in the mid-1990s suggests that changes were primarily driven by NPGO climate conditions rather than seabird prey abundance (Figure 4). This mechanism is likely controlled by a change in the timing of seasonal upwelling in the California Current system that is linked to NPGO.
The authors found correlations between food web dynamics and large-scale climate variability change over time, and the complex behavior of ENSO and NPGO are driving these patterns. The NPGO has strengthened in recent decades, while ENSO has shifted from eastern to central Pacific events.
Understanding how populations of marine species respond to environmental variability is essential for managing and predicting consequences of future climate change. Recently, ENSO has increased in frequency and shifted from eastern to central Pacific events. Central Pacific ENSO is connected to the variability of NPGO through changes in atmospheric circulation. Thus, a changing response in seabird reproduction may be linked to the recent changes in ENSO and intensification of NPGO. The bio-physical interactions in the North Pacific remain incredibly complex and this study shows that predictions based on correlations that remain the same in time may be inappropriate for describing the how certain species will respond to climate variability in the North Pacific in the future.
Hillary received her MS in oceanography from the University of Maine in 2014 and works in the Ecosystem Modeling Lab at the Gulf of Maine Research Institute in Portland, ME.
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