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Tracking wildlife migration has been historically difficult in the rugged terrain of Alaska. Researchers primarily rely on either surveys or GPS tracking to understand bird migration patterns. Both methods are expensive, either in terms of time or money. And the trackers are often too large or heavy.
One way to sidestep these common issues is to record audio from frequently used nesting grounds. Using birdsong allows researchers to unobtrusively study the animals, although there’s a downside. Each day produces a flood of audio recordings from multiple microphones placed around nesting grounds. It takes trained listeners endless hours to search the noisy soundscape for birdsong.
In a recently published paper in the journal Science Advances, U.S. researchers explain how they got around these tracking troubles. Columbia University ecologist Ruth Oliver and her fellow collaborators replaced the human ears with machine learning algorithms to listen to birdsong.
Oliver told VOA News, “Arrival times of migratory song birds is really important for their reproductive success. And obviously sending people to the Arctic to do field work is very expensive and takes a lot of time” — hence, the scientists’ interest in creating an automated method for tracking bird species.
Oliver and her colleagues focused on migratory songbirds who fly to northern Alaska during their mating season. These birds tend to chirp more frequently as soon as they reach the breeding grounds to attract a mate. Spring is short in Alaska and the birds must breed and hatch their clutch before winter.
The team of researchers recorded the springtime soundscape of northern Alaska for five sequential years. They placed microphones at four sites in the foothills of the Brooks Range, which recorded 1,200 audio hours.
However, Oliver admitted the recordings weren’t always perfect. “There’s a lot of other noise in these recordings” Oliver said. “Even in May in northern Alaska there’s lots of wind, lots of rain, and all of that is confounding when you’re listening to birds.”
The scientists fed hours of audio into two types of machine learning algorithms — one that used human expertise to help train it and one that relied solely on the collected audio. Both algorithms were based on the same model that’s used by applications like Siri and Alexa.
Oliver told VOA that in creating the human-supervised algorithm, she “wrote a little program to randomly sample about 1 percent of the data set” and then listened to 4-second clips. She scored these clips as either containing or not containing songbird vocalizations and then fed this information into the program.
Both algorithms were fairly accurate at estimating when the avian commuters arrived in the foothills. The models showed the importance of snowmelt for the arrival of the traveling birds. The human-trained model was slightly better at recognizing the relationship between weather conditions and bird calls, although neither model specifically tracked individual species.
This technique has great potential according to Emily Jo Williams, vice president of migratory birds and habitat at the American Bird Conservancy, “This kind of technique that allows you to survey populations in those remote areas is really exciting and could allow us to even discover new places where protection and conservation efforts are needed,” she said.
This study looked at nesting grounds near the Alaskan Arctic Refuge, which is a summer home for birds from nearly every continent. For example, the Northern Wheatear travels approximately 21,000 kilometers (13,000 miles) from Africa to summer in the refuge.
Williams told VOA, “We know from some research that some birds’ ranges have actually changed, and they’ve moved in response to what we think is a warming climate.” She went on to explain that “the timing of that migration has evolved over eons, and in large part it’s relative to what food sources are available over a particular time, what weather patterns are or aren’t favorable. So you could end up with bird migration out of sync with insect hatches or the phenology of plants that birds have a relationship to.”
Tools like the algorithm created in this study could be used to track how migratory patterns of many species may shift in response to climate change. Using machine learning is a new way to follow these shifting patterns in birds, insects and other animals. (VOA)
Hackers have stolen crypto tokens worth $120 million from Blockchain-based decentralised finance (DeFi) platform BadgerDAO. Several crypto wallets were drained before the platform could stop the cyber attack. In a tweet, Badger said it has received reports of unauthorised withdrawals of user funds. "As Badger engineers investigate this, all smart contracts have been paused to prevent further withdrawals. Our investigation is ongoing and we will release further information as soon as possible," the company said late on Thursday.
According to the blockchain security and data analytics Peckshield, the various tokens stolen in the attack are worth about $120 million, reports The Verge. According to reports, someone inserted a malicious script in the user interface (UI) of their website. Badger has retained data forensics experts Chainalysis to explore the full scale of the incident and authorities in both the US and Canada have been informed. "Badger is cooperating fully with external investigations as well as proceeding with its own," it said. DeFi is a collective term for financial products and services that are open, decentralised and accessible to anyone. DeFi products open up financial services to anyone with an internet connection and they are largely owned and maintained by their users. While the attack didn't reveal specific flaws within Blockchain tech itself, it managed to exploit the older "web 2.0" technology that most users need to use to perform transactions, according to reports. (IANS/ MBI)
(Keywords: crypto wallets, BadgerDAO, decentralised finance, Blockchain, 120 million, crypto tokens, Hackers)
A total of 120 top Bollywood and other celebrities are expected to attend the wedding of film stars Katrina Kaif and Vicky Kaushal which is scheduled on December 9 in Rajasthan, said Rajendra Kishan, the District Collector (DC) of Sawai Madhopur district of the state on Friday. The District Collector told mediapersons: "These 120 guests shall follow all COVID-19 protocols and fully vaccinated guests will get entry in the much-hyped celebrity wedding."
Kishan said that the organisers have been asked to strictly follow all Covid-19 protocols. Also, those who are not vaccinated, will not be allowed without the negative RT-PCR test report, he added. "We have been informed by organisers that a total of 120 guests are invited to the wedding and the events will take place between December 7 to December 10," he added.
Earlier at 10.30 a.m., Kishan called a meeting which was attended by administrative, police and forest department officials, hotel and event managers to ensure adequate arrangements for crowd control, smooth regulation of traffic, and law and order situation amid the VIP movement. The wedding venue Fort Barwara, that has been converted into a heritage hotel, is situated in the panchayat samiti Chauth Ka Barwara. The venue is around 22 km away from Sawai Madhopur and is around 174 km from Jaipur. Sawai Madhopur district is famous for the Ranthambore National Tiger Reserve and as per reports, the guests are likely to be taken for a tiger safari. (IANS/ MBI)
(Keywords: Rajasthan, December 9, Vicky Kaushal, Katrina Kaif, film stars, celebrities, Bollywood, Katrina-Vicky)
The National Centre for Biological Sciences (NCBS), which confirmed the first two cases of the Omicron variant in Bengaluru on Thursday, is continuously monitoring the situation in four cities - Bengaluru, Hyderabad, New Delhi, and Pune. The NCBS is a part of a consortium of national laboratories performing genomic surveillance across four city clusters. The consortium was established four months ago with support from The Rockefeller Foundation's Pandemic Prevention Institute, and is led by the Centre for Cellular and Molecular Biology (CCMB) in Hyderabad.
Dr Rakesh Mishra at the CCMB said on Friday that the consortium is continuously monitoring the situation in all the four cities and has upscaled its efforts to sequence as many samples as possible Apart from the CCMB and the NCBS, the consortium includes CSIR-Institute of Genomics and Integrative Biology - IGIB in New Delhi and the Pune Knowledge Cluster, Indian Institute of Science Education and Research (IISER), Pune, and CSIR-National Chemical Laboratory in Pune.
The first case of the Omicron variant was detected in South Africa and reported to the World Health Organization on November 24. | Unsplash
The consortium is focused on upscaling genomic surveillance as part of national efforts led by the INSACOG - Indian SARS-CoV-2 Genomics Consortium - to respond to the Covid-19 pandemic. The consortium intensified its sequencing efforts after the World Health Organisation announced Omicron as a Variant of Concern. Such an intensified effort enabled the Bengaluru team at the NCBS, a member laboratory of INSACOG, in collaboration with Strand Life Sciences and the Bruhat Bengaluru Mahanagara Palike (BBMP), to detect, rapidly sequence and verify the existence of the omicron variant in samples from two Covid-19 infected individuals.
They hope this will aid in a rapid response to contain the spread of variants of concern. Prof Satyajit Mayor from the NCBS conveyed the information to local and national authorities, and the Indian government released a statement on December 2, all within four days of receiving the samples. Both SARS-CoV-2 genomes have also been uploaded to the global repository for SARS-CoV-2 sequences, GISAID, so that they can be publicly available to the scientific community, the NCBS said. (IANS/ MBI)
(Keywords: Hyderabad, New Delhi, Pune, Bengaluru, The National Centre for Biological Sciences, Situation, NCBS, Omicron)