Daily Archives: July 13, 2022

Press Releases

07/11/2022

(HARTFORD, CT) Governor Ned Lamont today announced that Evolution, a live casino operator for digital platforms, has begun operating in Connecticut. The company, which has already hired 140 employees to work at its newly built studio in Fairfield, is expected to hire up to 400 total workers in Connecticut, offering technical, production, administrative and information technology positions, as well as security.

With the addition of Evolution, we are continuing to provide a modern, technologically advanced gaming experience that provides an elevated user experience for eligible residents and is competitive with our neighboring states, Governor Lamont said. Connecticut has proven to be a leader when it comes to the gaming economy going back decades, and this expansion allows those who want to participate to continue doing so, responsibly.

We are proud of the hard work our Gaming Division has done to ensure Evolutions facilities and offerings meet the high standards set by our regulations to create a safe and successful opportunity for live dealer games in Connecticuts online gaming marketplace, Connecticut Department of Consumer Protection Commissioner Michelle H. Seagull said. We encourage anyone who chooses to participate in this new form of online gaming to do so responsibly by monitoring their activity and setting limits for themselves utilizing the tools that are required to be available on these platforms.

Evolution began operations with a seven-day soft launch, authorized by the Connecticut Department of Consumer Protection, at 11:00 a.m. on Monday, July 11, 2022. Evolution will provide live dealer games on both the FanDuel and DraftKings iCasino platforms offered in Connecticut. During the soft launch, only blackjack and roulette tables will be available to a limited number of participants. The soft launch will transition seamlessly into the full launch at 11:00 a.m. on Monday, July 18, 2022, pending the resolution of any issues discovered in the soft launch.

The Connecticut Department of Consumer Protection will monitor the soft launch to ensure Evolutions games meet the states regulations for online gaming. Connecticut law requires Evolution to operate an in-state facility in order to offer live dealer games on Connecticut gaming platforms.

Information about gaming in Connecticut, including the most up-to-date statistics, is available at ct.gov/gaming.

Information on services available in Connecticut for those who may have a problem with gambling is available at portal.ct.gov/problemgaming. Information about self-exclusion is available at ct.gov/selfexclusion.

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Governor Lamont Announces Opening of Evolution Gaming Studio in Connecticut - CT.gov

ROME, July 12, 2022 (GLOBE NEWSWIRE) -- NetBet - one of Italys most popular online casinos - has introduced the best titles from Evolution to its players.

NetBet Italy is progressively forging their identity as an exceptional online casino for the Italian market, continuously evolving their product offering to bring players the best games in the industry. Evolution are a well-respected developer whose products already have a strong following across NetBets international markets.

Evolution are experts in creating Live Dealer and RNG games that appeal to all kinds of players. This partnership with NetBet Italy will make highlights from their catalogue, including Live Roulette, Live Blackjack and Lightning Roulette, available to fans of Live Dealer games.

NetBet Italys PR manager, Claudia Georgevici, said: Evolution are a fantastic brand that were delighted to bring into the fold. Were certain that our players will enjoy their unique brand as part of their NetBet playing experience.

For more information contact pr@NetBet.it

About NetBet.itNetBet.it is a single-member BPG srl site, founded in 2008. It is one of the first Italian portals specialising in online gaming and is licensed by ADM. With access to thousands of industry-leading casino games and daily sports events, NetBet.it has evolved into one of Italy's favourite online gaming brands.

For more information please visit: https://www.netbet.it

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NetBet Italy partners with Evolution - GlobeNewswire

For more than a century, insect-eating plants have captivated biologists, but how plants gained the capacity to catch and eat live prey has mostly remained a mystery.

Scientists from Salk and Washington University in St. Louis have now studied the molecular underpinnings of plant carnivory and discovered evidence that it developed from defense mechanisms used by plants.

(Photo : Andi Superkern/Unsplash)

The study described how calcium molecules move dynamically within cells in the leaves of carnivorous plants in reaction to touch from living prey.

It was published on July 11 in Proceedings of the National Academy of Sciences (PNAS).

Changing calcium levels cause leaves to move in order to grab prey, perhaps by producing more defense-related hormones, as per ScienceDaily

The information advances scientists' knowledge of how plants interact with their surroundings.

In order to live in nutrient-poor environments, plants like the spoon-leaved sundew (Drosera spatulata) probably evolved carnivory.

However, because sundews are difficult to produce and their DNA has only recently been decoded, researchers have had trouble understanding how carnivory functions at the cellular level.

Additionally, they were unaware of how carnivorous plants evolved prey-capture-related characteristics including leaf motion and the release of digesting enzymes.

Carl Procko, the co-first author of the research and a staff scientist in Salk's Plant Molecular and Cellular Biology Laboratory, asserted that carnivorous sundew plants are not model organisms.

The scientists had to learn new procedures to closely investigate the plants because only a small number of labs throughout the world had previously been able to genetically change them.

To conduct this work, the researchers used genetic methods to visualize the dynamic changes in calcium molecules in the leaves as insect prey touched down on them and were subsequently trapped by sticky secretions.

Calcium signaling is essential for non-carnivorous plants in several ways, including activating the jasmonate defense pathway to ward off pest insects.

Electrical activity, a crucial component of prey capture in some carnivorous plants, including sundews, is similarly reacted to by jasmonic acid.

The researchers wondered if the carnivorous habit of the sundew would also require this similar defense mechanism found in non-carnivorous plants.

The team discovered that as the leaf bent inward, encasing the insect in digestive secretions, changes in calcium within the plant cell were necessary for the activation of genes generally targeted by jasmonic acid.

Sundew leaves exhibited less bending when offered non-living prey and when their calcium channels were blocked, according to the researchers.

These results support the hypothesis that jasmonic acid is involved in insect digestion and show how calcium facilitates insect prey-capture reflexes.

Also Read: Carnivorous Plant Gives Unique Insight on 'Junk' DNA

The evolution of generally mild-mannered floral plants into homicidal meat-eaters is one of botany's greatest unanswered mysteries, and carnivorous plants are currently experiencing another major turning point, as per theSmithsonian Magazine

More recently, developments in molecular science have aided researchers in understanding crucial mechanisms underlying the carnivorous lifestyle, such as how a flytrap snaps so quickly and transforms into an "intestine" to absorb its prey's leftovers after crushing insects.

But the fundamental question remained: how did evolution give these meat-eating dietary outlaws the ability to do so?

Despite being strange, carnivory has undergone numerous evolutionary changes during the more than 140 million years that flowering plants have existed.

According to Tanya Renner, an evolutionary biologist at Penn State, the adaption appeared independently at least 12 times.

The necessity to discover a different supply of essential nutrients catalyzed evolution each time.

Carnivorous plants thrive in ecosystems deficient in the nitrogen and phosphorus necessary for growth, such as swamps and bogs, nutrient-poor bodies of water, and thin tropical soils.

Both, as well as other nutrients plants, require to thrive, are abundant in insects and other tiny invertebrates that are high in protein.

Many aspects of the carnivorous way of life are still guarding their genetic secrets.

However, research on two of its most gruesome components-digestion and absorption-is showing how evolution repurposed already-existing genes, giving some new jobs to do while giving others new functions and the occasional change to better fit their new responsibilities.

The same genes have frequently been reused in plants that separately developed carnivory.

Beyond digestion, evolution has a propensity to acquire and modify existing tools.

The trap must transfer the smaller molecules created as chitin, proteins, and DNA are broken down from the outside environment to the interior of the plant.

Related Article: Taste for Meat: Scientists Trace Genetic Route of Carnivorous Plants

2022 NatureWorldNews.com All rights reserved. Do not reproduce without permission.

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Researchers Study the Molecular Basis of Carnivorous Plants and Found the Evolution of Them Through the Past - Nature World News

Grime artist Jammers basement studio Courtesy of the Museum of London

Originally an underground sound, grime has gone mainstream in Britainand since its creation, it has become hugely influential for artists around the world.

Now, a new free exhibition celebrates the scenes origins and evolution. Grime Stories: From the Corner to the Mainstream at the Museum of London features photos, videos and memorabilia documenting two decades of grime.

The display is co-curated byRoony RiskyRoadz Keefe, who the museum calls one of grimes early documentarians. In particular, his DVD series Risky Roadz helped propel artists to fame in the years after the genres creation. Per theGuardians Joseph Patterson, much of what is on display comes from the archives of Keefe and others like him.

Grime is one of those genres that once its in you, it never leaves, Keefe tells the Guardian.

The museum originally asked Keefe, a London cab driver by day, to conduct interviews about the grime scene in the back of his taxi. Now, a series of films, which include Keefes interviews with influential grime artists like Skepta andDJ Slimzee, are at the center of the exhibition,BBC News reports.

Its a big thing, you know, says Keefe to the New York Times Desiree Ibekwe. You never think youre going to end up in a museum.

Grime emerged in the early 2000s among artists in east London who wanted a sound that was uniquely theirs. It was both an evolution from and reaction to U.K. garage music, as the Times writes. Other British forms of rap had become overly Americanized, some felt, with slang borrowed from across the Atlantic.

While the genres definition has evolved over the years, grime music generally has a tempo of 140 beats per minute; the Guardian describes it as post-punk angst on waxa heady mix of dancehall, jungle and U.K. garage, inspired by Jamaican ragga toasting and the storytelling of U.S. hip-hop.

Artists in the scene align themselves with grime crews that produce and perform music together. One of the most notable crews isRoll Deep, formed in the early 2000s, which has included performers likeWiley,Danny Weed,Breeze, Skepta andDizzee Rascal.

In recent years, grime has seen a resurgence with the arrival of new artists likeStormzy, who the Times calls grimes most successful breakout. In 2017, the Labour Partys Jeremy Corbyn enlisted grime artists toencourage the public to vote for him, per the Times. In 2019, IKEA featured grime M.C. D Double E in a Christmas commercial.

This is a monumental moment in the U.K., especially for Black British culture, Jammer, an early grime artist, tells the Guardian.

From the early days, Jammers familys basementknown as the Dungeonwas a critical place for grime artists, and the new exhibition features many references to the space.

When grime began, he adds, it was the only thing we knew how to do to make a better life for ourselves. Grime is like our therapy: you go into it with your pain, get your lyrics out and then you get better and you learn.

Grime Stories: From the Corner to the Mainstream is on view at the Museum of London through December.

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Inside the Evolution of Grime Music | Smart News - Smithsonian Magazine

Remarks on the residual color patterns in the Kitadani Freshwater Bivalves

Residual color patterns in the form of visible pigmentation on fossil molluscan shells are generally uncommon2,3. In the Paleozoic to Mesozoic fossil records, the color patterns were limited to marine species3, which are preserved as black to dark-colored bands running on the shell surface as melanin pigments20,21. The black to dark-colored stripes on the shells of the Kitadani Freshwater Bivalves resemble the color patterns in some extant freshwater bivalves, suggesting that the dark bands are residual color patterns remaining as melanin pigments. Consequently, the Kitadani Freshwater Bivalves represents the oldest and second fossil record of residual color patterns among fossil freshwater bivalves.

The residual color patterns of the Kitadani Freshwater Bivalves resemble the color patterns of extant freshwater bivalves in terms of width, number, and distribution of the colored bands. Both the Kitadani Freshwater Bivalves and extant freshwater bivalves examined in this study consist of two types of color patterns: stripes along the growth lines and radial rays tapered toward the umbo. Notably, the former pattern is similar among all the species examined, as it forms in the peripheries of prominent growth lines occurring periodically. In the latter pattern, however, the morphology and distribution of the bands are slightly different between the Kitadani Freshwater Bivalves and the extant species. The Kitadani Freshwater Bivalves exhibits relatively distinct and wide radial rays running roughly parallel to the lengths of the sculpture elements (radial plications and/or wrinkles), while the extant species bear obscure and fine radial rays running diagonally to the lengths of the sculpture elements. Nonetheless, the taxa with V-shaped sculpture elements (wrinkles, ribs or arranged nodules) lack or bear ambiguous radial rays, whether extant (e.g., Triplodon spp., Indochinella spp. and Tritogonia spp.)13,15,22 or extinct (Trigonioides tetoriensis).

The resemblance of the color patterns between the Kitadani Freshwater Bivalves and the extant unionids possibly resulted from the phylogenetic constrains. Each of the three species of the Kitadani Freshwater Bivalves belongs to a separate family (Trigonioides tetoriensis: Trigonioididae, Plicatounio naktongensis: Plicatounionidae, and Matsuomtoina matsumotoi: Pseudohyriidae) in the order Trigoniida19. Trigoniida in turn, forms the subclass Palaeoheterodonta with Unionida23. This raises a possibility that the color patterns observed in the Kitadani Freshwater Bivalves and the extant unionids is inherited from their most recent common ancestor. In other words, these color patterns, stripes along the growth lines and radial rays tapered toward the umbo, may be the apomorphy for Palaeoheterodonta. In fact, some extant trigoniid species belonging to Neotrigonia exhibit color pattern similar to those in the Kitadani Freshwater Bivalves and extant unionids in this study (e.g. Neotrigonia margaritacea)1.

Interestingly, the coloration of color patterns is quite different between unioniids (green to blue colorings) and trigoniids (red to yellow colorings), and the oldest known color patterns of the Palaeoheterodonta (Myophorella nodulosa, a marine species of Trigoniida from the Oxfordian of the Early Jurassic) appears different (concentric rows of patches)10 from those of the Kitadani Freshwater Bivalves or the extant unioniids. These observations suggest that colorations evolved independently, in contrast to the color patterns, between Trigoniida and Unionida, and that Trigoniida more diverse color patterns than Unionida did in the Palaeoheterodont evolutionary history. Although further examination of the fossil record for the residual colors and color patterns in Palaeoheterodonta is essential, it is plausible that the habitat differences may have caused such discrepancy in the colorations and color patterns between Trigoniida (mainly marine) and Unionida (freshwater) in spite of the phylogenetic constrains.

The other possible interpretation of the color pattern similarity between the Kitadani Freshwater Bivalves and extant Unionida, is the convergent evolution. One potential factor that may have caused this convergent evolution of the color patterns is an adaptation to their habitats. In general, much of the convergent evolution in animals occurs through the morphological evolution in response to their habitats24. Similarly in mollusks, shell colors and their patterns are generally influenced by their habitats2,6,25. Considering marine mollusks, the shell colors and their patterns have great diversity due to varying habitat environments, especially in coral reeves that exhibit various colors and complex ecosystem2,6. Conversely, in the freshwater ecosystem, the environmental colors are relatively monotonous with rocks, sand, mud, and green algae8, and such habitat conditions are likely indifferent between the Mesozoic and Cenozoic. As a result, the freshwater bivalves retained simple and monotonous color patterns for adapting to such environments throughout their evolution.

Another conceivable factor to explain the convergent evolution in the color patterns of the studied freshwater bivalves is the selection pressure by visual predators. In general, the shell colors and their patterns in bivalves act as camouflages against the predators2,7,8,26,27,28. Previous studies have demonstrated that extant freshwater bivalves are preyed upon by crayfish, fish, birds, reptiles, and mammals29,30. Because shell colors in freshwater bivalves tend to be greenish, such colors may be an adaptation against visual predators for blending into the freshwater sediments on which abundant greenish phytoplanktons occur2,8. Therefore, the evolutionary conservatism in color patterns of freshwater bivalves may result from camouflages into freshwater microenvironments, which has been advantageous against visual predators since the late Early Cretaceous.

The above discussion assumes that the visual predators of freshwater bivalves remained similar for at least 120 million years. Which animals could have been potential threads to the Kitadani Freshwater Bivalves, and, in turn, the Early Cretaceous freshwater bivalves? Among the extant visual predators of the freshwater bivalves, those whose lineages were present in the Early Cretaceous include crustaceans (especially brachyuran decapoda31), fish, lizards, turtles, crocodiles, birds, and mammals. Among them, the fossil record of durophagous lizards and mammals can be traced back only to the Late Cretaceous32,33. Conversely, lines of fossil evidence suggest that some fish34,35, turtles36, and crocodiles35 fed on molluscan invertebrates during the Early Cretaceous, and the Kitadani Freshwater Bivalves indeed occurs with abundant lepisosteiform scales, testudinate shells and crocodile teeth. Additionally, at least one Early Cretaceous avian species with crustacean gut contents can be attributed to the durophagous diet37, and the Kitadani Formation has yielded avialan skeletal remains38, and footprints39,40. Therefore, fish, turtles, crocodiles, and birds are likely candidates for visual predators of the Early Cretaceous freshwater bivalves, and have remained so until present. Additionally, while crustaceans have not been identified in the Kitadani Formation, they flourished in the Early Cretaceous and their remains occur with the fossil freshwater bivalves of the time elsewhere31. Thus, crustaceans may have also played a role as visual predators of the freshwater bivalves since the Early Cretaceous.

In addition to the crustaceans, fishes, turtles, crocodiles and birds, the visual predators of the Early Cretaceous freshwater bivalves likely include extinct lineages. For example, some pliosauroid plesiosaurs are suggested as being durophagous34, although the freshwater members of the group are considered endemic41 and less likely to be a major thread to the Early Cretaceous freshwater bivalves. Another extinct candidate is non-avian dinosaurs. Ornithischians are suggested to have possessed a dietary flexibility including the durophagy. For instance, well-preserved hadrosaurid coprolites from the Late Cretaceous of Montana, U.S.A. include sizeable crustaceans and mollusks, possibly suggesting that the Cretaceous freshwater mollusks were consumed by these herbivorous dinosaurs42. In addition, some basal ceratopsian psittacosaurids are hypothesized for the durophagy based on the predicted large bite force in the caudal portion of the toothrow43. Among saurischians, some oviraptorosaurian theropods are indicated to consume mollusks with hard shells based on their mandibular features44. While hadrosaurids, psittacosaurids, and oviraptorosaurians have not been identified in the Kitadani Formation, psittacosaurids, and oviraptorosaurians are common elsewhere in the Early Cretaceous of East Asia45,46, and hadrosauroid Koshisaurus is present in the formation47. Because dinosaurs occupied a niche of large terrestrial predators throughout the Mesozoic, they may have acted as one of major mollusk consumers in absence of large lizards and mammals in the Early Cretaceous ecosystem. Thus, the predation pressure by visual predators to the freshwater bivalves in the Early Cretaceous is likely similar to that in the present. Consequently, one of evolutionary adaptations of the freshwater bivalves against such pressure has remained to camouflage in the phytoplankton-rich sediments, leading to the long-term evolutionary conservatism of their color patterns.

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Case study of the convergent evolution in the color patterns in the freshwater bivalves | Scientific Reports - Nature.com

A new study out of South Africa could rewrite certain aspects of humankinds evolutionary origin story.

The study hinges on an innovative fossil aging technique called cosmogenic nuclide dating. It shows that the fossil record of an early human-like hominid called Australopithecus africanus stretches back 3.8 million years, making the species one million years older than previously thought.

The findings, published in the journal PNAS, are significant because they show Australopithecus africanus is just as old as a different hominid species called Australopithecus afarensis.

Au. afarensis was a type of bipedal hominin common to east Africa. The first skeleton of this species was unearthed in 1974 and is now known as the famous Lucy skeleton.

Since paleoanthropologist Donald Johannson exhumed Lucys remains, many scientists have pointed to the remains as the primary intermediary between modern-day humans and our ancient primate cousins. But these new findings make it harder to say, with any degree of certainty, that human beings evolved directly from Lucys species.

We found that Australopithecus africanus is in the same age range as Australopithecus afarensis, which is Lucys species in east Africa, the studys lead author Dr. Darryl Granger told MeatEater. Lucys species started showing up at about the same time, about 3.8 million years ago, but Lucy herself is 3.2 million years old, so these fossils weve dated are older than Lucy herself but not older than her species.

According to Granger, the two species of ancient bipedal hominids are contemporaries, meaning they emerged and existed around the same time.

People used to think about the [human family] tree as being very linear, meaning one species leads to another, Granger said. One of the traditional views is that Lucys species, afarensis, evolved into africanus in South Africa, but that cant happen because theyre the same age. They both have an older common ancestor, and they both showed up around the same time.

Granger has been working in Sterkfontein, South Africaa complex cave site known for its high concentration of Au. africanus remainson and off since the early 2000s. Around 2003, he started to suspect that the fossils there were much older than most anthropologists believed.

Before Granger made his discovery, the Au. africanus fossils of Sterkfontein were dated at only 2.1 to 2.6 million years old. That would have put them on the earth at the same time as the genus homo, which emerged around 2.8 million years ago. As a result, Au. africanus was ruled out as an early precursor to modern humans.

That narrative is shifting now, thanks largely to Grangers work, which relied on the more up-to-date cosmogenic nuclide dating method.

The method measures the amount of cosmic ray exposure in the sedimentary matrix that surrounds the Au. africanus fossils of Sterkfontein.

Cosmic rays originate in outer space, and they leave a traceable imprint on the earth's surface when they interact with certain elements. Once the remains of Au. africanus and the surrounding sediment were buried deep within the Sterkfontein cave complex they were no longer being exposed to cosmic rays. Granger and his team have determined the point when that cosmic ray exposure ceased, thus assigning the new age to Sterkfonteins Au. africanus fossils.

You can think about the cosmogenic nuclides kind of like a sun tan, Granger said. The longer youre exposed, the darker you get. And then if you go inside and stay inside for months, your tan fades away. The same thing happens to these rocks if they get washed into a cave. Whatever they built up at the surface decays away by radioactivity, so you can see how much is left after theyve been buried and figure out how long theyve been in a cave.

While Grangers work updates our understanding of the age and origin of the Au. africanus speciesand increases the likelihood that africanus is in fact one of our earliest ancestorsit doesnt change what we know about the bipedal hominids day-to-day life.

According to Granger, the species wasnt known for using stone tools. While it may have relied on insects and small animals to supplement a fruit, root, and grass-heavy diet, africanus didnt eat meat on a regular basis or engage in organized hunting.

They would have been eating a lot of different things that were around in their environment but mostly plants, he said. The big transition to relying on meat and marrow was later, when you see the transition from australopithecus to homo. Thats when the brains expanded, and you started seeing stone tools probably used for processing animal carcasses, for getting at bone marrow inside the bones, which is really energy-rich.

The evolution from australopithecus to homo, and the corresponding leap in brain size, was driven by the adoption of meat-rich diets, Granger said. Compared to human brains, the brains of the australopiths were relatively smallmore akin to that of a modern chimpanzee.

As for his most recent finding, Granger said that much of the feedback hes received so far has been supportive. But because the study is still so new and its implications so significant, hes anticipating some criticism and resistance from the broader scientific community.

Ive been working in Sterkfontein before, and theres been some resistance to earlier aging from deeper in the cave. People can come up with scenarios where youve got young fossils in old sediment, but that doesnt work here, he said. This paper, in a way, is a response to that resistance, and its reinforcing the idea that these [South African] australopithecines are old. I welcome criticism and other people working at the site. Thats the way science happens. We all try to poke holes in each others work. Its part of the process. Well wait and see.

Originally posted here:

A New Study Will Change the Way We View Human Evolution - MeatEater

A 1.4 million-year-old fragment of fossilized skull could provide a new understanding of how the human face developed, a team of paleontologists has said.

The fossil, a piece of jawbone belonging to an ancient ancestor of homo sapiens and possibly the oldest archaic human fossil found in Europe, was found in the Atapuerca Mountains in northern Spain on June 30.

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The fragment discovered by a doctoral student, according to the Atapuerca Foundation, a non-profit that runs the site is thought to be older than the remains of a species named homo antecessor, or pioneer man, that was found in a nearby cave at Atapuerca in 1997 and was thought to be 850,000 years old.

Experts believe the new find announced on Friday is related to a fragment of jawbone which was found a few feet away at the same site in 2007 that dates back 1.2 million years, but was not classified as any particular species due to a lack of evidence.

"The first days of the month of July 2022 will be part of the history of the field of human evolution," the Atapuerca Foundation said in a statement.

After much cleaning and analyzing, the team concluded that the fossil, found at a site called Sima del Elefante, or elephant chasm, corresponds to a human upper jaw and belonged to an archaic human among the first hominins to travel to Europe from Africa.

"The excavations at [level 7] of the Sima del Elefante cave site have surprised us with an exceptional find. It is the partial face of a human being, whose age may be around 1.4 million years," the statement said.

Excavations in Atapuerca were started by caving enthusiasts in the the 1950s, before systematic digs in the 1970s found a series of key fossils. The team still excavating the area now consists of nearly 300 experts from 22 countries across 30 scientific disciplines.

The findings have yet to be published in any peer-reviewed format.

There is an ongoing debate among scientists over when in evolutionary history the modern face emerged.

"We will have a unique opportunity to advance in the answer to this question," the foundation said.

Further work is being done to analyze stone and plant matter, to get a better understanding of the climate in which the first European settlers lived.

The Atapuerca project seeks to answer controversial questions surrounding the study of hominins a group including humans and our extinct ancestors such as how and when early human forebears moved from Africa to colonize Eurasia.

Homo sapiens are the last surviving members of the human lineage, homo, which dates back about 2 million years. But there were once several and about 400,000 to 500,000 years ago some of them split from groups living in Africa and came to Eurasia where they developed characteristics associated with our short, stocky cousins, the Neanderthals.

Patrick Smith is a London-based editor and reporter for NBC News Digital.

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Scientists say they may have found a fossilized jaw bone belonging to the oldest human ancestor in Europe - NBC News

One question that branches across every generation of Pokmon is the need for fans to ask if there is a new evolution for Eevee being added, something that has popped back up ahead of Scarlet and Violets release.

This is not only because Eevee has been one of the most popular Pokmon since it was introduced in Kanto, but also because it has received multiple new forms outside of the original three it started with in generation on.

From Espeon and Umbreon in Johto to simply Sylveon in Kalos, Eeveelutions have been known to span generations. And, even though The Pokmon Company and Game Freak have turned Eevee and its evolutions into even more of a marketing focal point in recent years, we still havent had a new one added since X and Y released in 2013.

Game Freak never really confirms just what Pokmon will be present in each new generation until marketing for the games really kicks off, hence why in the second SV trailer we only saw a handful of new Pokmon introduced alongside the starters. And, now that leaks and rumors are so prevalent surrounding each Pokmon release, it is hard to truly know what is real until an official reveal is made or the games actually launch.

For SV, one reputable leaker that has been around since Sun and Moon on Chinese forums claims that there will not be a new Eeveelution in the upcoming games. They didnt specify exactly where the information came from, but they did specifically say that Sylveon remains the newest evolution for Eevee.

Because this information isnt coming from an official source, there is still a chance that it isnt true and Eevee will get its fabled ninth Eeveelution alongside generation ninebut this does put a slight damper on the hopes of those Eevee-faithful.

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Will there be a new Eevee evolution in Pokmon Scarlet and Violet? - Dot Esports

Over the last 10 years I have written several times about the attributes of our North American native, Echinacea purpurea, or what we commonly refer to as a coneflower. These tough perennials mix well with Ornamental Grasses, Sedums, Lavender, Black-eyed Susan Daisies and really, just about any summer blooming perennial that likes a hot, dry, location. And while they have been a staple on most gardens, traditionally they only came in purple or white. That is, until breeders crossed them with a yellow flowering species and that is when all hell broke loose, in mostly a good way of course.

In the early days of Echinacea breeding there were many new introductions that proved to be less than reliable for northwest gardeners. Our wet soils and relatively mild winters could cause them to rot and not return in spring. Also, some of those early introductions were too tall and spindly and would tend to flop over in a summer rain. I cant begin to tell you how many new selections I have managed to kill over the last 10 years this is an unfortunate side effect of having severe plant lust, but one that I am happy to endure. Fortunately, most of the newer offerings are much more compact and sturdier and only grow to 18 to 24 inches tall and as wide, so they make a nice compact clump.

These days in garden centers, you can find cone flowers in warm shades from yellow to orange to red and all the tropical variations in between, not to mention fun double forms. Some of the original introductions like the Meadowbrite and Big Sky series have been replaced with newer forms such as the Sombrero series. There are literally dozens of choices to be had on garden center benches this time of year and they are all worth making space for in your garden. The most recent ones to catch my attention are from the Evolution Series and they are being grown by one of our favorite suppliers, Monrovia Growers. Here are their descriptions of the color options they are producing for this summer.

Evolution Colorific An enchanting green cone at the center of every bloom, framed by dense petals in a lovely palette of pink hues. Lush foliage and sturdy, upright stems create a beautiful backdrop for the continuous profusion of blooms from late spring through fall. Stunning in beds, borders and containers

Evolution Embers Sparks Bright, sunny blooms for easy color from late spring through fall. Semi-double, golden yellow petals surround showy center cones. A cutting garden essential, perfect for containers or mixed perennial borders. Allow dried flower heads to remain on plants for wintering songbirds.

Evolution Fever This one sports large red blooms on a tidy, well-branching plant that makes it ideal for adding bold color to mixed borders, containers, and cutting gardens.

Evolution Fiesta A riot of color with spicy coral-pink flowers that age to softer shades. New flowers emerge throughout summer, providing a lively display.

Evolution Yellow Falls Lemon yellow petals arch downward from showy center cones. A cutting garden essential, and perfect for containers or borders.

Look for these new introductions (not all may be available) along with multiple other choices from other growers. And remember to plant them in full sun and good drainage where they should return year after year and provide you with generous bouquets of flowers all summer long. Keep on gardening, summer is perfect for adding more plants to the garden!

Steve Smith represents Sunnyside Nursery in Marysville and can be reached at sunnysidenursery@msn.com.

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Study population and song recordings

All animal procedures were carefully reviewed by the Williams College IACUC (WH-D), the Bowdoin College Research and Oversight Committee (200918), and the University of Guelph Animal Care Committee (08R601), and were carried out as specified by the Canadian Wildlife Service (banding permit 10789D).

We studied Savannah sparrows (Passerculus sandwichensis) at the Bowdoin Scientific Station on Kent Island, New Brunswick, Canada (44.5818N, 66.7547W). Since 1988, individuals nesting within a 10ha study area in the middle of the island (3070 pairs each year; part of a larger population of 350500 males breeding on Kent Island and two adjacent islands) have been colour-banded to facilitate visual identification, and complete demographic information is available for birds on the study site (though not for the entire population) for the years 19892004 and 20092013. Because of strong natal and breeding philopatry51, birds hatched on the study site itself represent 4080% of adult breeders in that area, and because of the systematic banding program, ages are known. Each year adds a new generation to the population, with yearlings making up approximately half of the adult breeding males. The birds banded and recorded on the study site are estimated to make up 1020% of the Savannah sparrow population on Kent Island and two nearby islands.

Details of the recording methods used in this study (covering the years 1980, 1982, 1988-9, 1993-8, and 200313) can be found elsewhere36,49. Using digitally generated sound spectrograms (using SoundEdit Pro and Audacity), birds were scored as having either a) high note cluster=a final introductory segment interval including at least two different note types, or b) a click train=one or more introductory segment intervals including at least two clicks and no other note types, or c) both features36 (see Supplementary Fig.1 for a full description of note types). Although a small proportion of birds (mean=8.3%) did not include either feature in their songs (such birds either had no feature in the introductory segment intervals or one non-click note type in the final interval), we did not include this option in the model and omitted these birds from summaries of the data. We did not include data after the breeding year 2013 because of we began an experimental field tutoring study in the summer of 201364.

We used a dynamic, discrete time model which allowed us to focus our analysis to specific time points within the year that are related to song learning (the beginning and end of the breeding season). These were: (1) the returnof older birds between breeding seasons, (2) the recruitment of young birds singing newly crystallized songs in the spring, and (3) reproduction, resulting in the addition of juveniles during the summer breeding season.

Because survival data were not available for every year during the time span we studied, we captured the variation in survival rates observed in the field57 by using a binomial distribution centered on the average historical survival rate for each age class (addressing the possibility that cultural drift resulting from random differences in survival rates was responsible for the shift in song features). The model incorporates stochasticity to capture the variation in population dynamics and return rates by assigning parameter values for survival and return rates from empirically generated probability distributions.

We did not include spatial distribution of song variants in the model; although spatial patterns can be important for the dynamics of language loss58, territories with birds singing click trains and high note clusters were intermixed and no spatial structure was apparent (Fig.3).

The model assumes that males choose which features to incorporate into the introductory sections of their songs during song development. Individuals fall into one of six mutually exclusive classes of male Savannah sparrows. The classes are defined by (1) the birds developmental stage in the song learning process: juvenile (J, the first year, when the song is plastic) or adult (A, after the first spring, when the song is crystallized), and (2) the variant or variants sung as part of the birds introduction (high note clusters, click trains, or both). Denoting note high note clusters with X and click trains with C, the adult classes are therefore AX, AC, and AXC, and the juvenile classes are JX, JC, and JXC. The sum of the individuals in these classes is the total male population.

We used two times during each year late spring and late summer to correspond to stages in song development (Fig.5). At a given time t, when breeding is underway in the late spring, the male population consists entirely of adults singing crystallized song, and therefore each juvenile class is empty. At the end of the summer, the population of males has been augmented by juveniles, which are initially assigned to the same variant class as their fathers. To capture these dynamics, we define an intermediate time step, denoted ti. Time t+1 then corresponds to the following breeding season (late spring), when juvenile males hatched the previous year have completed song development, crystallized their songs, and joined the adult class.

We used two age classes (J=juvenile and A=adult) and three classes of introductions (C=click trains, X=high note clusters, and XC=both). In the late spring of a given year (time=t), only adult males are present. In late summer, those adults have bred and both they and juvenile males are present; at this intermediate time (ti) each male is initially allocated the same introduction type as his father (solid lines). Then, as song development progresses and juvenile males can be influenced by other tutors, they may retain their initial introduction type or switch to either of the other two types (dashed lines) before they crystallize their songs late in the following spring (time=t+1), and join the breeding cohort, which also includes adult males from the previous year who returned to breed again.

In the late summer the male population increases with the addition of juveniles hatched that year, some of which will return to join the singing population the following year; survivors will return to breed within a few hundred meters of where they hatched51. To fit the observed historical decline in the Kent Island population57, the total number of returning juveniles, r (including both those hatched on site and those immigrating from nearby populations at time), follows a Poisson distribution where m=33.6 .182x and x is the number of years since 1980 (this function results in a decline of 5 males per decade; the initial number on the study site used in the model, 70, was extrapolated from historical data). The size of each returning juvenile class at time ti then takes the form:

$${{{{{{rm{JY}}}}}}}_{{{{{{{rm{t}}}}}}}^{{{{{{rm{i}}}}}}}} sim {{{{{rm{Poisson}}}}}}left(mright)frac{{{{{{rm{A}}}}}}{{{{{{rm{Y}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}}{{{{{{rm{A}}}}}}{{{{{{rm{X}}}}}}}_{{{{{{rm{t}}}}}}}+{{{{{rm{A}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{rm{t}}}}}}}+{{{{{rm{AX}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{rm{t}}}}}}}}$$

(1)

for each Y {X, C, XC}.

After the following winter, the proportion of surviving adults at time t+1 follows a binomial distribution where the mean survival rate s=0.48 is derived from historical data. Therefore, each adult class takes the form:

$${{{{{rm{A}}}}}}{{{{{{rm{Y}}}}}}}_{{{{{{rm{t}}}}}}+1} sim {{{{{rm{Binomial}}}}}}left({{{{{rm{AY}}}}}},{{{{{rm{s}}}}}}right)* {{{{{rm{A}}}}}}{{{{{{rm{Y}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}$$

(2)

At the beginning of the next breeding season, juveniles complete song learning64, choosing which variant to crystallize as part of the song, and enter an adult song class; thus all of the juvenile classes disappear at t+1. Which adult class juveniles join depends on separate learning functions for each of the two variants, X for the high note cluster and C for the click train. The function takes values between 0 and 1 and gives the probability of crystallizing a song form during the transition from natal year to breeding, depending upon the frequency-dependent bias and selection parameters (see below). These functions define the proportion of features that appear in the next generation as compared to that of the previous generation. Therefore we have:

$${{{{{rm{A}}}}}}{{{{{{rm{X}}}}}}}_{{{{{{rm{t}}}}}}+1}={left({{{upphi }}}_{{{{{{rm{X}}}}}}}right)}^{2}{{{{{rm{J}}}}}}{{{{{{rm{X}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+{left(1-{{{upphi }}}_{{{{{{rm{C}}}}}}}right)}^{2}{{{{{rm{J}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+{{{upphi }}}_{{{{{{rm{X}}}}}}}left(1-{{{upphi }}}_{{{{{{rm{C}}}}}}}right){{{{{rm{JX}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+{{{{{rm{A}}}}}}{{{{{{rm{X}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}$$

(3)

$${{{{{rm{A}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{rm{t}}}}}}+1}={left(1-{{{upphi }}}_{{{{{{rm{X}}}}}}}right)}^{2}{{{{{rm{J}}}}}}{{{{{{rm{X}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+{left({{{upphi }}}_{{{{{{rm{C}}}}}}}right)}^{2}{{{{{rm{J}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+left(1-{{{upphi }}}_{{{{{{rm{X}}}}}}}right){{{upphi }}}_{{{{{{rm{C}}}}}}}{{{{{rm{JX}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+{{{{{rm{A}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}$$

(4)

$${{{{{rm{A}}}}}}{{{{{{rm{XC}}}}}}}_{{{{{{rm{t}}}}}}+1}=2{{{upphi }}}_{{{{{{rm{X}}}}}}}left(1-{{{upphi }}}_{{{{{{rm{X}}}}}}}right){{{{{rm{J}}}}}}{{{{{{rm{X}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+2{{{upphi }}}_{{{{{{rm{C}}}}}}}left(1-{{{upphi }}}_{{{{{{rm{C}}}}}}}right){{{{{rm{J}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}+({{{upphi }}}_{{{{{{rm{X}}}}}}}{{{upphi }}}_{{{{{{rm{C}}}}}}}left(1-{{{upphi }}}_{{{{{{rm{X}}}}}}}right)left(1-{{{upphi }}}_{{{{{{rm{C}}}}}}}right){{{{{rm{JX}}}}}}{{{{{{rm{C}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}})+{{{{{rm{A}}}}}}{{{{{{rm{XC}}}}}}}_{{{{{{{rm{t}}}}}}}_{{{{{{rm{i}}}}}}}}$$

(5)

The sum of probabilities defining all of song crystallization outcomes for the songs of fathers with song type X is:

$${left({{{upphi }}}_{{{{{{rm{X}}}}}}}right)}^{2}+{left(1-{{{upphi }}}_{{{{{{rm{X}}}}}}}right)}^{2}+2{{{upphi }}}_{{{{{{rm{X}}}}}}}left(1-{{{upphi }}}_{{{{{{rm{X}}}}}}}right)=1$$

(6)

To define how young males song learning is influenced by the songs they hear, we used learning curves based on type III Holling response curves59 which provide a means to numerically capture functional responses. In our model, the type III curve models the response of juvenile to the song form of adults in the population based on two variables: (1) frequency-dependent bias that favors one form based on its prevalence within the adult population, and (2) selection that favors a particular form of the song.

The learning curves, x for the high note cluster and c for the click train, are modified forms of the type III Holling response curve):

$${{{upphi }}}_{{{{{{rm{x}}}}}}}=frac{{x}^{{{{{{rm{beta }}}}}}}/{{{{{rm{sigma }}}}}}}{{(1-x)}^{{{{{{rm{beta }}}}}}}+({x}^{{{{{{rm{beta }}}}}}}/{{{{{rm{sigma }}}}}})}$$

(7)

and

$${{{upphi }}}_{{{{{{rm{c}}}}}}}=frac{{{{{{rm{sigma }}}}}},{c}^{{{{{{rm{beta }}}}}}}}{{(1-c)}^{{{{{{rm{beta }}}}}}}+{{{{{rm{sigma }}}}}}{{c}}^{{{{{{rm{beta }}}}}}}}$$

(8)

where x is the proportion of the high note cluster within the population, c is the proportion of the click train within the population, is frequency-dependent bias (favoring learning the novel or retaining the common variant), and is selection on the novel variant (a preference for learning the variant that is not dependent on frequency of the variant and includes factors such as prestige bias, success bias, status, and content bias). Note that the two learning curves do not have identical equations, because selection is not frequency-dependent. In these equations, >1 corresponds to conformist selection, and when <1 the rare form is favored. Values of >1 correspond to selection for a novel variant and values of <1 correspond to selection against a novel variant. The parameters and allow us to test the relative roles of frequency-dependent bias and cultural selection, as well as various combinations of the two by using a single function giving the probability that social learning will result in a juvenile male crystallizing a particular song variant.

Males that sang both high note clusters and click trains (the AXC class) could be interpreted in one of two ways within this framework:

Two-trait: by counting each variant individually, so that a bird singing both variants is counted twice in calculations of variant frequencies (once for high note clusters, and once for click trains), while a bird singing one form is counted only once. In this scenario, frequencies were calculated as (time subscripts omitted for clarity):

$${{{{{{rm{P}}}}}}}_{{{{{{rm{C}}}}}}}=frac{{{{{{rm{AC}}}}}}+{{{{{rm{AXC}}}}}}}{{{{{{rm{AC}}}}}}+{{{{{rm{AX}}}}}}+2{{{{{rm{AXC}}}}}}}$$

(9)

and

$${{{{{{rm{P}}}}}}}_{{{{{{rm{X}}}}}}}=frac{{{{{{rm{AX}}}}}}+{{{{{rm{AXC}}}}}}}{{{{{{rm{AC}}}}}}+{{{{{rm{AX}}}}}}+2{{{{{rm{AXC}}}}}}}$$

(10)

Blended trait: each bird was counted once (birds that sang a single variant were weighted twice as much as those that sang both traits). In this scenario, frequencies were calculated as:

$${{{{{{rm{P}}}}}}}_{{{{{{rm{C}}}}}}}=frac{2{{{{{rm{AC}}}}}}+{{{{{rm{AXC}}}}}}}{2({{{{{rm{AC}}}}}}+{{{{{rm{AX}}}}}}+{{{{{rm{AXC}}}}}})}$$

(11)

and

$${{{{{{rm{P}}}}}}}_{{{{{{rm{X}}}}}}}=frac{2{{{{{rm{AX}}}}}}+{{{{{rm{AXC}}}}}}}{2({{{{{rm{AC}}}}}}+{{{{{rm{AX}}}}}}+{{{{{rm{AXC}}}}}})}$$

(12)

As most males singing click trains in the 1980s and early 1990s also sang a high note cluster, we assumed that the innovators songs included both forms. We know that click trains first appeared in the population between 1983 and 1987, as they were absent in 1982 recordings and present in 1988 recordings. Prior to 1983, all adults sang high note clusters and so belonged to the AX class. We modeled the appearance of click trains in the population with the term in, which represented the number of innovators (which we modeled as entering the population in class AXC, see the next section), and was added in any year from 1983 to 1987. To maintain populations at consistent levels, we subtracted the number of innovators from the AX class in the year the innovation was introduced.

First, we assumed that interstitial notes, whether high note clusters, click trains, or both, represented a single trait. We tested this assumption by running the model with either (1) the blended trait or (2) treating click trains and high note clusters as two distinct traits (see Supplementary Table2 and Supplementary Fig.2); the blended trait model fit the data better.

We know from the corpus of recordings that click trains were not observed in 1980 or 1982, when high note clusters were the prevalent form. Click trains were first recorded in 1988. Because we do not have recordings for the period spanning 1983 to 1987, each of these years is potentially the time of the initial introduction. We used the earliest possible year, 1983, as the default, because we observed potential precursors of the click train in 1982 songs. We also modeled the appearance of initial innovations for the years 1984 through 1987 (Supplementary Table3 and Supplementary Fig.3).

The number of innovators (individuals that sang the click train in the first year it appeared on the study site) is unknown. We chose a default value of 2 males (2.9% of the study population of 70) for two reasons. First, innovations we have observed in other segments of Savannah sparrow songs initially appeared in the songs of 2or 3 individuals. Second, this mutation rate, =0.029 per song per year, is in the range found in previous work on the introduction of innovations in learned songs: 0.001 to 0.035 per year in U.K. chaffinches85, and ~ 0.057 in New Zealand chaffinches86 This value is also in the middle of the range used to model human cultural evolution (0.004 to 0.128)87. We varied the number of innovators from 1 to 8 (=0.014 to =0114) to assess the effect of this parameter on the models results (see Supplementary Table4 and Supplementary Fig.4).

Our models thus used, as default values, two innovators, appearing in 1983, that sang both click trains and high note clusters as a blended trait, and we tested the effects on the modeling results by varying these default values.

The model was implemented in the R88 package POMP89 (Partially Observed Markov Processes), using embedded C code. We performed a grid search over a range of the parameters and (from 0.5 to 2.0 in 0.05 steps for each parameter if not otherwise stated) and calculated the estimated the log likelihood for each parameter combination. We used an initial burn-in of 50 years prior to the first year for which we compared the model to existing data (1980). We repeated this analysis for each set of initial conditions (year the innovation was introduced, and blended vs. two-trait categorization for birds that sang both high note clusters and click trains). We visualized the model space with heat map plots prepared using MatLab, and identified the maximum likelihood estimate (MLE) and the corresponding 95% confidence intervals. Using the best fit parameters (those that corresponded to the MLE), we then ran the model again 50 times to generate average and 95% CI trajectories for frequencies of song variants and plotted them in the same manner as the observed field data.

We tested the responses of Savannah sparrows on their territories in early July of 2011 (when most pairs were feeding young or beginning a second clutch) to song segments with click trains that included different numbers of clicks. None of the songs of 39 birds recorded on the study site in 2011 included high note clusters. The mean number of clicks within click trains was 3.93, ranging from 0 (3 birds) to 7 (3 birds), with a mode of 4 clicks in a train (n=16). All of the subjects of the playback study would have had the opportunity to hear click trains ranging from 0 to 7 clicks, but would not have been familiar with high note clusters. Because comparisons of responses to songs with click trains and high note clusters would have been confounded by the issue of familiarity, we only tested subjects responses to the number of clicks in a train. (A test of the efficacy of click trains and high note clusters in hand-reared birds that had not been exposed to either form might address the question of how preferences may be shaped by social learning).

The stimuli were constructed from high-quality recordings of introductory sections from the songs of 12 different males to produce different 12 stimulus sets, to avoid pseudoreplication. The introductory sections of the twelve songs were originally composed of 58 introductory notes, between which were 13 click trains that included 37 clicks. Each of these introductory segments was extracted and then digitally altered (using Audacity, audacityteam.org) to produce a set of four different stimuli that included 0, 2, 4, or 7 clicks in each click train. The introductory notes, the temporal spacing of the introductory notes and the length of the entire introductory segment was the same for each stimulus within a set. Clicks were added to a train by duplicating existing clicks and adjusting them to be evenly spaced within the interval between introductory notes. Clicks were removed by replacing clicks at the end of a train with silence. Since introductory notes are substantially longer (mean=67ms) than clicks (mean=2ms), a change of one click in a click train stimulus represented a change of, on average, 0.91% in the signal duration (taking into account that adding one click to a train meant adding one click to all instances of that train within a stimulus). Introductory notes are also substantially louder than clicks, and so the overall change in the sound intensity within different stimuli was very small. To the human ear, longer click trains make the intervals between the louder, longer introductory notes sound somewhat raspier than shorter click trains, but the difference is subtle.

Each of 25 male subjects was tested with all four stimuli from one set. Each trial started with a primer, a stimulus consisting of introductory notes without interstitial notes55. Two minutes after the birds response ended, the first test stimulus was presented for two minutes (at 12second intervals). The next stimuli were presented in succession, with a delay of two minutes after the birds response ended for each stimulus. Stimuli were presented in a randomized order, and each stimulus set was used at least twice. The response duration and behaviours of males (crouching with head feathers flattened close to the skull, aggressive displays48 and vocalizations90) were noted. We used duration, measured as time from the end of the stimulus presentation until the male ceased responding (defined as moving 20m or more away from the speaker, or singing a full and loud song, or engaging in feeding or preening behaviour), as our primary measure of male response55. Because the strength of the response varied across birds, we normalized response durations for each individual bird in Fig.4c. To correct for a rightward skew in the distribution, we log-transformed the raw response duration measure and assessed the relationship between response duration and number of clicks (F1,73=10.97, P<0.005), using a generalized mixed-effects model implemented with the lme4 package91 in R which included the identity of the subject (F24,73=3.84, P<0.000001) as well as the trial order (F1,73=0.012, P>0.9) as random effects. We did not record songs produced during stimulus playback; we observed an average of 0.6 songs per trial, which would not have provided a large enough sample size for analysis.

Females did not always respond to the playback stimuli. When they did respond (in 11 of 25 trials) their responses differed from those of males: females typically stood erect rather than crouching, elevated their crest feathers instead of flattening them, and were never observed to give aggressive wing flutters or vocalizations but rather hopped towards the speaker while peering about alertly. Because female responses to other song stimuli presented in previous studies used the postures and behaviours typical of male aggressive responses, we interpret the approach with an erect posture and crest as having a different valence: investigative/approach rather than aggressive. We noted both which stimuli the females approached and which stimulus they first approached and evaluated the effects of click number with a Chi-squared test.

Further information on research design is available in theNature Research Reporting Summary linked to this article.

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