Evaluating The Ocean Cleanup, a Marine Debris Removal Project in the North Pacific Gyre, Using SWOT Analysis

Plastic pollution in oceans, also known as marine debris, is a growing problem at local and global scales. Anthropogenic marine debris poses a serious threat to many marine species, both through physical harm such as ingestion or entanglement and by carrying toxins and pathogens. This debris accumulates in oceanic gyres, concentrating these effects in some specific areas. In addition, marine debris may have devastating impacts on tourism and fishing-based economies, especially where ocean currents direct this debris. Recently, a nonprofit organization called The Ocean Cleanup proposed the first large-scale in situ marine debris removal project. The Ocean Cleanup is a project attempting to use large, floating, semi-fixed screens to harness ocean currents and accumulate debris, where it can be efficiently collected and disposed of or recycled. The project currently is working on implementing itself in the “Great Pacific Garbage Patch,” in the North Pacific Gyre. We examine this project case, as it is the first organization attempting to clean up marine debris at this scale. Understanding the potential efficacy and limitations of The Ocean Cleanup Project as a case study can give critical insights into how other projects could be created in the future to address marine plastic pollution worldwide. Using SWOT (strengths, weaknesses, opportunities, and threats) analysis to assess a marine debris cleanup can inform both a nuanced evaluation of the specific case as well as provide a means to explore marine debris as a complex, global environmental problem.

Non-stationary climate–salmon relationships in the Gulf of Alaska

Studies of climate effects on ecology often account for non-stationarity in individual physical and biological variables, but rarely allow for non-stationary relationships among variables. Here, we show that non-stationary relationships among physical and biological variables are central to understanding climate effects on salmon ( Onchorynchus spp.) in the Gulf of Alaska during 1965–2012. The relative importance of two leading patterns in North Pacific climate, the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO), changed around 1988/1989 as reflected by changing correlations with leading axes of sea surface temperature variability. Simultaneously, relationships between the PDO and Gulf of Alaska environmental variables weakened, and long-standing temperature–salmon and PDO–salmon covariance declined to zero. We propose a mechanistic explanation for changing climate–salmon relationships in terms of non-stationary atmosphere–ocean interactions coinciding with changing PDO–NPGO relative importance. We also show that regression models assuming stationary climate–salmon relationships are inappropriate over the multidecadal time scale we consider. Relaxing assumptions of stationary relationships markedly improved modelling of climate effects on salmon catches and productivity. Attempts to understand the implications of changing climate patterns in other ecosystems might also be aided by the application of models that allow associations among environmental and biological variables to change over time.

The North Pacific Gyre Oscillation and Mechanisms of Its Decadal Variability in CMIP5 Models

Based on the Simple Ocean Data Assimilation (SODA) product and 37 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) database, the North Pacific Gyre Oscillation (NPGO) and its decadal generation mechanisms are evaluated by studying the second leading modes of North Pacific sea surface height (SSH) and sea level pressure (SLP) as well as their dynamical connections. It is found that 17 out of 37 models can well simulate the spatial pattern and decadal time scales (10–30 yr) of the NPGO mode, which resembles the observation-based SODA results. Dynamical connections between the oceanic mode (NPGO) and the atmospheric mode [North Pacific Oscillation (NPO)] are strongly evident in both SODA and the 17 models. In particular, about 30%–40% of the variance of the NPGO variability, which generally exhibits a preferred time scale, can be explained by the NPO variability, which has no preferred time scale in most models. Two mechanisms of the decadal NPGO variability that had been proposed by previous studies are evaluated in SODA and the 17 models: 1) stochastic atmospheric forcing and oceanic spatial resonance and 2) low-frequency atmospheric teleconnections excited by the equatorial Pacific. Evaluation reveals that these two mechanisms are valid in SODA and two models (CNRM-CM5 and CNRM-CM5.2), whereas two models (CMCC-CM and CMCC-CMS) prefer the first mechanism and another two models (CMCC-CESM and IPSL-CM5B-LR) prefer the second mechanism. The other 11 models have no evident relations with the proposed two mechanisms, suggesting the need for a fundamental understanding of the decadal NPGO variability in the future.