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Planet’s ocean-plastics problem detailed in 60-year data set

Researchers find evidence of rising plastic pollution in an accidental source: log books for planktonmonitoring instruments. Matthew Warren 

Scientists have uncovered the first strong evidence that the amount of plastic polluting the oceans has risen vastly in recent decades — by analysing 60 years of log books for plankton-tracking vessels. 

Data recorded by instruments known as continuous plankton recorders (CPRs) — which ships have collectively towed millions of kilometres across the Atlantic Ocean — show that the trackers have become entangled in large plastic objects, such as bags and fishing lines, roughly three times more often since 2000 than in preceding decades.

This is the first time that researchers have demonstrated the rise in ocean plastics using a single, longterm data set, says Erik van Sebille, an oceanographer at Utrecht University in the Netherlands. “I’m excited that this has been finally done,” he says. The analysis was published on 16 April in Nature Communications. 

 Although the findings are unsurprising, long-term data on ocean plastics had been scant: previous studies looked mainly at the ingestion of plastic by sea creatures over shorter timescales, the researchers say.

Fishing for data

CPRs are torpedo-like devices that have been used since 1931 to survey plankton populations, by filtering the organisms from the water using bands of silk. Today, volunteer ships such as ferries and container ships tow a fleet of CPRs around the world’s oceans. 

(…)Each time a ship tows a CPR, the crew fills in a log book and notes any problems with the device. So Ostle and her colleagues looked through all tow logs from the North Atlantic between 1957 and 2016, to determine whether plastic entanglements have become more common.

Evidence analysis

(…)Van Sebille says that because the study focused on large plastic items, it doesn’t reveal much about the quantity of microplastics — fragments fewer than 5 millimetres long — in the oceans. These tiny contaminants come from sources such as disposable plastic packaging, rather than from fishing gear.

Nevertheless, he adds, the study demonstrates that fisheries play a major part in plastic pollution, and will provide useful baseline data for tracking whether policy changes affect the levels of plastic in the oceans. “As fisheries become more professional, especially in the North Sea, hopefully we might see a decrease,” he says.

Source: https://www.nature.com/articles/d41586-019-01252-0 (adapted).

Access: April 20th, 2019 

TEXT II

What to Know About the Controversy Surrounding the Movie Green Book

Depending on who you ask, Green Book is either the pinnacle of movie magic or a whitewashing sham. 

The film, which took home the prize for Best Picture at the 91st Academy Awards, as well as honors for Mahershala Ali as Best Supporting Actor and Nick Vallelonga, Brian Currie and Peter Farrelly for Best Original Screenplay, depicts the burgeoning friendship between a black classical pianist and his ItalianAmerican driver as they travel the 1960s segregated South on a concert tour. But while Green Book was an awards frontrunner all season, its road to Oscar night was riddled with missteps and controversies over its authenticity and racial politics. 

Green Book is about the relationship between two real-life people: Donald Shirley and Tony “Lip” Vallelonga. Shirley was born in 1927 and grew up in a well-off black family in Florida, where he emerged as a classical piano prodigy: he possessed virtuosic technique and a firm grasp of both classical and pop repertoire. He went on to perform regularly at Carnegie Hall— right below his regal apartment—and work with many prestigious orchestras, like the Chicago Symphony and the New York Philharmonic. But at a time when prominent black classical musicians were few and far between due to racist power structures, he never secured a spot in the upper echelons of the classical world. (African Americans still only make up 1.8 percent of musicians playing in orchestras nationwide, according to a recent study.) 

Vallelonga was born in 1930 to working-class Italian parents and grew up in the Bronx. As an adult he worked as a bouncer, a maître d’ and a chauffeur, and he was hired in 1962 to drive Shirley on a concert tour through the Jim Crow South. The mismatched pair spent one and a half years together on the road — though it’s condensed to just a couple of months in the film — wriggling out of perilous situations and learning about each other’s worlds. Vallelonga would later become an actor and land a recurring role on The Sopranos. 

In the 1980s, Vallelonga’s son, Nick, approached his father and Shirley about making a movie about their friendship. For reasons that are now contested, Shirley rebuffed these requests at the time. […]

(Source: from http://time.com/5527806/green-book-movie-controversy/)

TEXT 1 below, retrieved and adapted from https://chroniclingamerica. loc.gov/lccn/sn83035487/1851-06-21/ed-1/seq-4/ on July 9th, 2018.

Text 1 

                    Women’s rights convention – Sojourner Truth

      One of the most unique and interesting speeches of the convention was made by Sojourner Truth, an emancipated slave. It is impossible to transfer it to paper or convey any adequate idea of the effect it produced upon the audience. Those only can appreciate it who saw her powerful form, her whole-souled, earnest gesture, and listened to her strong and truthful tones. She came forward to the platform and addressing the President said with great simplicity:

      "May I say a few words?" Receiving an affirmative answer, she proceeded: I want to say a few words about this matter. I am a woman's rights. I have as much muscle as any man and can do as much work as any man. I have plowed and reaped and husked and chopped and mowed, and can any man do more than that? I have heard much about the sexes being equal. I can carry as much as any man, and can eat as much too, if I can get it. I am as strong as any man that is now. As for intellect, all I can say is, if a woman has a pint, and a man a quart -- why can't she have her little pint full? You need not be afraid to give us our rights for fear we will take too much; -- for we can't take more than our pint will hold. The poor men seem to be all in confusion, and don't know what to do. Why children, if you have woman's rights, give it to her and you will feel better. You will have your own rights, and they won't be so much trouble. I can't read, but I can hear. I have heard the bible and have learned that Eve caused man to sin. Well, if a woman upset the world, do give her a chance to set it right side up again. The Lady has spoken about Jesus, how he never spurned woman from him, and she was right. When Lazarus died, Mary and Martha came to him with faith and love and besought him to raise their brother. And Jesus wept and Lazarus came forth. And how came Jesus into the world? Through God who created him and the woman who bore him. Man, where was your part? But the women are coming up blessed be God and a few of the men are coming up with them. But man is in a tight place, the poor slave is on him, woman is coming on him, he is surely between a hawk and a buzzard.

Reference: Robinson, M. (1851, June 21). Women’s rights convention: Sojourner Truth. Anti-slavery Bugle, vol. 6 no. 41, Page 160.

TEXT II

The backlash against big data

[…]

Big data refers to the idea that society can do things with a large body of data that weren’t possible when working with smaller amounts. The term was originally applied a decade ago to massive datasets from astrophysics, genomics and internet search engines, and to machine-learning systems (for voice-recognition and translation, for example) that work well only when given lots of data to chew on. Now it refers to the application of data-analysis and statistics in new areas, from retailing to human resources. The backlash began in mid-March, prompted by an article in Science by David Lazer and others at Harvard and Northeastern University. It showed that a big-data poster-child—Google Flu Trends, a 2009 project which identified flu outbreaks from search queries alone—had overestimated the number of cases for four years running, compared with reported data from the Centres for Disease Control (CDC). This led to a wider attack on the idea of big data.

The criticisms fall into three areas that are not intrinsic to big data per se, but endemic to data analysis, and have some merit. First, there are biases inherent to data that must not be ignored. That is undeniably the case. Second, some proponents of big data have claimed that theory (ie, generalisable models about how the world works) is obsolete. In fact, subject-area knowledge remains necessary even when dealing with large data sets. Third, the risk of spurious correlations—associations that are statistically robust but happen only by chance—increases with more data. Although there are new statistical techniques to identify and banish spurious correlations, such as running many tests against subsets of the data, this will always be a problem.

There is some merit to the naysayers' case, in other words. But these criticisms do not mean that big-data analysis has no merit whatsoever. Even the Harvard researchers who decried big data "hubris" admitted in Science that melding Google Flu Trends analysis with CDC’s data improved the overall forecast—showing that big data can in fact be a useful tool. And research published in PLOS Computational Biology on April 17th shows it is possible to estimate the prevalence of the flu based on visits to Wikipedia articles related to the illness. Behind the big data backlash is the classic hype cycle, in which a technology’s early proponents make overly grandiose claims, people sling arrows when those promises fall flat, but the technology eventually transforms the world, though not necessarily in ways the pundits expected. It happened with the web, and television, radio, motion pictures and the telegraph before it. Now it is simply big data’s turn to face the grumblers.

(From http://www.economist.com/blogs/economist explains/201 4/04/economist-explains-10)