Natural cycles in South Pacific Gyre strength and the Southern Annular Mode.

The South Pacific Gyre (SPG) plays a vital role in regulating Southern Hemisphere climate and ecosystems. The SPG has been intensifying since the twentieth century due to changes in large scale wind forcing. These changes result from variability in the Southern Annular Mode (SAM), causing warming along the eastern SPG which affects local ecosystems. However, our understanding of SPG variability on timescales greater than several decades is poor due to limited observations. Marine sediment cores are traditionally used to determine if recent ocean trends are anomalous, but rarely capture centennial variability in the southwest Pacific and limit our understanding of SPG variability. Here we capture centennial SPG dynamics using a novel high-resolution paleocirculation archive: radiocarbon reservoir ages (R) and local reservoir corrections (∆R) in SPG deep-sea black corals. We find black coral R and ∆R correlates with SAM reconstructions over 0-1000 cal BP and 2000-3000 cal BP. We propose this correlation indicates varying transport of well-ventilated subtropical waters resulting from SPG and SAM interactions. We reconstruct several 'spin up' cycles reminiscent of the recent gyre intensification, which has been attributed to anthropogenic causes. This implies gyre strength and SAM show natural co-variability on anthropogenic timescales which should factor into future climate projections.

Synergistic effects of harvest and climate drive synchronous somatic growth within key New Zealand fisheries.

Fisheries harvest has pervasive impacts on wild fish populations, including the truncation of size and age structures, altered population dynamics and density, and modified habitat and assemblage composition. Understanding the degree to which harvest-induced impacts increase the sensitivity of individuals, populations and ultimately species to environmental change is essential to ensuring sustainable fisheries management in a rapidly changing world. Here we generated multiple long-term (44-62 years), annually resolved, somatic growth chronologies of four commercially important fishes from New Zealand's coastal and shelf waters. We used these novel data to investigate how regional- and basin-scale environmental variability, in concert with fishing activity, affected individual somatic growth rates and the magnitude of spatial synchrony among stocks. Changes in somatic growth can affect individual fitness and a range of population and fishery metrics such as recruitment success, maturation schedules and stock biomass. Across all species, individual growth benefited from a fishing-induced release of density controls. For nearshore snapper and tarakihi, regional-scale wind and temperature also additively affected growth, indicating that future climate change-induced warming and potentially strengthened winds will initially promote the productivity of more poleward populations. Fishing increased the sensitivity of deep-water hoki and ling growth to the Interdecadal Pacific Oscillation (IPO). A forecast shift to a positive IPO phase, in concert with current harvest strategies, will likely promote individual hoki and ling growth. At the species level, historical fishing practices and IPO synergized to strengthen spatial synchrony in average growth between stocks separated by 400-600 nm of ocean. Increased spatial synchrony can, however, increase the vulnerability of stocks to deleterious stochastic events. Together, our individual- and species-level results show how fishing and environmental factors can conflate to initially promote individual growth but then possibly heighten the sensitivity of stocks to environmental change.

Poor transferability of species distribution models for a pelagic predator, the grey petrel, indicates contrasting habitat preferences across ocean basins.

Species distribution models (SDMs) are increasingly applied in conservation management to predict suitable habitat for poorly known populations. High predictive performance of SDMs is evident in validations performed within the model calibration area (interpolation), but few studies have assessed SDM transferability to novel areas (extrapolation), particularly across large spatial scales or pelagic ecosystems. We performed rigorous SDM validation tests on distribution data from three populations of a long-ranging marine predator, the grey petrel Procellaria cinerea, to assess model transferability across the Southern Hemisphere (25-65°S). Oceanographic data were combined with tracks of grey petrels from two remote sub-Antarctic islands (Antipodes and Kerguelen) using boosted regression trees to generate three SDMs: one for each island population, and a combined model. The predictive performance of these models was assessed using withheld tracking data from within the model calibration areas (interpolation), and from a third population, Marion Island (extrapolation). Predictive performance was assessed using k-fold cross validation and point biserial correlation. The two population-specific SDMs included the same predictor variables and suggested birds responded to the same broad-scale oceanographic influences. However, all model validation tests, including of the combined model, determined strong interpolation but weak extrapolation capabilities. These results indicate that habitat use reflects both its availability and bird preferences, such that the realized distribution patterns differ for each population. The spatial predictions by the three SDMs were compared with tracking data and fishing effort to demonstrate the conservation pitfalls of extrapolating SDMs outside calibration regions. This exercise revealed that SDM predictions would have led to an underestimate of overlap with fishing effort and potentially misinformed bycatch mitigation efforts. Although SDMs can elucidate potential distribution patterns relative to large-scale climatic and oceanographic conditions, knowledge of local habitat availability and preferences is necessary to understand and successfully predict region-specific realized distribution patterns.