Investigating Spatiotemporal Distribution and Habitat use of Poorly Understood Procellariiform Seabirds on a Remote Island in American Samoa.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Scales of spatial heterogeneity of plastic marine debris in the northeast pacific ocean.

Plastic debris has been documented in many marine ecosystems, including remote coastlines, the water column, the deep sea, and subtropical gyres. The North Pacific Subtropical Gyre (NPSG), colloquially called the "Great Pacific Garbage Patch," has been an area of particular scientific and public concern. However, quantitative assessments of the extent and variability of plastic in the NPSG have been limited. Here, we quantify the distribution, abundance, and size of plastic in a subset of the eastern Pacific (approximately 20-40°N, 120-155°W) over multiple spatial scales. Samples were collected in Summer 2009 using surface and subsurface plankton net tows and quantitative visual observations, and Fall 2010 using surface net tows only. We documented widespread, though spatially variable, plastic pollution in this portion of the NPSG and adjacent waters. The overall median microplastic numerical concentration in Summer 2009 was 0.448 particles m(-2) and in Fall 2010 was 0.021 particles m(-2), but plastic concentrations were highly variable over the submesoscale (10 s of km). Size-frequency spectra were skewed towards small particles, with the most abundant particles having a cross-sectional area of approximately 0.01 cm(2). Most microplastic was found on the sea surface, with the highest densities detected in low-wind conditions. The numerical majority of objects were small particles collected with nets, but the majority of debris surface area was found in large objects assessed visually. Our ability to detect high-plastic areas varied with methodology, as stations with substantial microplastic did not necessarily also contain large visually observable objects. A power analysis of our data suggests that high variability of surface microplastic will make future changes in abundance difficult to detect without substantial sampling effort. Our findings suggest that assessment and monitoring of oceanic plastic debris must account for high spatial variability, particularly in regards to the evaluation of initiatives designed to reduce marine debris

Numerical concentrations of microplastic from neuston samples and sub-surface samples.

<p>M indicates manta tows, B indicates bongo tows, and the number refers to the station. Boxes are middle 50% of the data, with the thick line denoting the median. Whiskers indicate 5^th and 95^th percentile of the data, and hollow circles indicate maximum and minimum values. Sample sizes are n = 8 for each manta tow box plot and n = 6 for each bongo tow boxplot, for a total of n = 32 manta tows and n = 24 bongo tows.</p

Comparison of plastic debris concentrations from visual and net tow data.

<p>Hollow circles indicate stations with visual observations and manta tow stations within 25(n = 23). Solid circles indicate median plastic abundance for visual observations and manta tow stations taken on the line sampling patterns within 9 km of each other. Lines extending from solid circles are bootstrap 95% confidence intervals. Data for solid circles is given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080020#pone-0080020-t002" target="_blank">Table 2</a>. Spearman's rank correlation rho = 0.603, p = 0.001. Regression line fit using Theil-Sen single median method.</p

Microplastic size spectra.

<p>Histogram of microplastic cross-sectional areas in A) Summer 2009 (n = 30,518) and B) Fall 2010 (n = 1,572). Figure shows all particles collected by manta tow. Visual observations are not included.</p

Dry masses of microplastic and zooplankton by location and time of day.

<p>A) Dry mass of microplastic; B) Dry biomass zooplankton; C) Ratio of plastic dry mass to zooplankton dry mass. Dry masses are given in mg m⁻². Boxes are middle 50% of the data, with the line denoting the median. Whiskers indicate 5^th and 95^th percentiles of the data, and hollow circles indicate maximum and minimum values. Abbreviations are North Pacific Subtropical Gyre (NPSG), transition region (TR), and California Current (CC), but water masses should be considered highly approximate. Time of day is abbreviated to D = day, C = crepuscular, and N = night. Only data from Summer 2009 are shown. Sample sizes are as follows: NPSG-D = 48, NPSG-C = 12, NPSG-N = 30, TR-D = 9, TR-N = 6, CC-D = 5, CC-C = 3, CC-N = 6.</p

Number of samples necessary to detect changes in microplastic concentration.

<p>A) The number of samples necessary (x-axis) to detect a percentage increase in the abundance of microplastic (y-axis) with a certain power (z-axis). For example, using a power of 80%, detection of a 50% increase in microplastic would require a sample size of n = 240. Analysis is based on surface microplastic data from Summer 2009. B) The number of samples necessary to reduce standard deviation of surface microplastic abundance. Dashed line is n = 119, the number of surface microplastic samples collected in Summer 2009. Dotted line is n = 28, the number of surface samples collected in Fall 2010. Analysis is based on surface microplastic data from Summer 2009 and Fall 2010.</p

Scale-dependence of variance in microplastic concentration and surface biophysical variables.

<p>A) Microplastic numerical concentration; B) Sea surface temperature; C) Sea surface salinity; D) Sea surface fluorescence. Dots are the values of the empirical semivariogram and the lines are a description of the data trends. A is fitted with a linear model, and B–D with Gaussian models. Data are shown for Summer 2009 only since sample size in Fall 2010 was insufficient for this analysis.</p

Particle concentration anomalies vs. wind speed anomalies.

<p>A) Summer 2009; and B) Fall 2010. Particle density was measured in surface manta net tows, and wind speed recorded by on-ship instrumentation during particle sampling. Sample sizes for Summer 2009 are n = 119 and for Fall 2010 n = 28. No line is shown due to poor fit with both polynomial linear, polynomial quadratic models, with less than 20% of the particle anomaly explained by wind anomalies.</p

Numerical concentrations of macrodebris and microdebris at four intensively sampled stations in the North Pacific Subtropical Gyre.

<p>Data is from line pattern deployed on August 15, 2009 proceeding west from 34°3.4′N, 141°22.4′W (designated by (2) in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080020#pone-0080020-g001" target="_blank">Fig. 1</a>). The line consisted of 4 stations of 5 repeated manta tows, for a total of 20 manta tows. The four stations were 18 km apart. Visual transect sampling of plastic macrodebris was performed between tow stations, with macrodebris observations for 9 km on either side of given station assigned to that station. Macrodebris concentrations were not statistically different among stations (Kruskal-Wallis test p>0.05). Microdebris concentration from the net tows were statistically different among stations (Kruskal-Wallis test p = 0.002), which was caused by the difference between station 1 and 3 (Nemenyi-Damico-Wolfe-Dunn test, p<0.001). Microplastic concentrations between the other net tow stations were not significantly different (Nemenyi-Damico-Wolfe-Dunn test, p>0.05).</p