Category Archives: Evolution

The automotive industry is a very interesting one to watch. You see all sorts of new trends and ideas emerge from there, and theres often a trickle-down effect on wider areas of society. The technology seen in the auto industry will eventually find its way to other industries, improving our lives.

Regardless, we want to look at how drastically the industry has evolved in the last twenty years alone. Since the turn of the century, we have seen loads of tech and engineering innovations that have changed the way the modern car looks and operates. Take two cars one that was made in the year 2000, and one made in 2021 and look at how different they are. A 20-year-old car is hardly classified as a classic motor, yet it feels archaic compared to the modern vehicles of today.

So, how have things changed and evolved? Lets take a look

Something so simple, yet a crucial part of every single production car. Headlamps guide the way in dark or dreary conditions, and theyve undergone an overhaul in the last two decades. At the start of the 2000s, we only just saw the gradual implementation of LED headlamps. Nowadays, theyre in basically every car. They offer a brightness that exceeds traditional halogen or high-intensity-discharge headlamps, with more flexibility.

Modern headlamps can actually turn on or off individual LED lights within them, based on how dark it is outside. It ensures that drivers will always get as much light as they need, improving safety and your driving comfort.

Over the years, the suspension system in cars has undergone dramatic improvements. Looking back twenty years ago, suspensions werent as bad as they were when cars were first introduced to the public. You can get some classic cars from the 80s that feel like youre constantly driving along speedbumps, even when the road surface is flat!

Still, improvements have been made, and you typically see these in modern-day muscle cars. The Ford Mustang is the king of the muscle category, and you can find Mustang coilovers that revolutionize the suspension. They add more stability to the ride, letting the car sit lower while avoiding any rollover around corners. In short, modern-day suspension kits are much better as they soften impacts and make every road feel smoother.

Not so much an improvement to the practicality of a car, but something that has drastically changed nonetheless. In older cars, you had to make do with a car radio. Not only that, but you had to deal with an awful signal from the antenna, which cut out all the time.

Fast forward a few years, and we had CD players in cars how fun! Towards the early 2000s, there were MP3 and Bluetooth capabilities. These days, you have an entire infotainment system at your disposal. Were talking touch screens, WiFi connectivity and even the ability to play games in some cars.

Its one of the biggest differences, but it begs the question; why? The info part we can understand modern cars provide far more information for you than older ones. You have live maps helping you plot your route with traffic updates, you can find out what the weather will be like during your journey, and so on. But, why has car entertainment changed to the point where video games can be played? Whats the point? Nobody gets in their car to be entertained we do it to drive, and the fewer distractions we have, the better.

Perhaps it sounds grouchy, but couldnt the money have been better spent on improving other aspects of a car? Or, you couldve saved money on the cars production, making it cheaper for us to buy!

Without a doubt one of the most significant advancements in the auto industry is the improvement in both electric and hybrid technologies. Again, if we think back to the year 2000, youd struggle to find many cars on the roads that were completely electric. The technology existed, but it was hard to make a car that was both as practical as a traditional one, and only needed electricity to power it.

We had hybrid technology, but that was still in its relatively early stages. Over the last two decades, both technologies have flourished, leading to drastic changes and improvements. Nowadays, we see more brands with hybrid and electric cars than ever before. Perhaps the biggest upgrade has been electric motors themselves. They are now powerful enough to compete with supercar combustion engines, yet practical enough to handle long journeys.

Of course, we also have to note the improvements in electric car infrastructure across the world. More charging points at gas stations and parking lots make it easier for electric vehicles to be practical.

Speaking of technology, car tech has gotten a lot smarter than it once was. We have pretty much always had cruise control, but before it would just set a speed and you would need to steer the car. Now, smart technology has incorporated sensors and radars to mean you can literally set some cars to cruise control and they drive within the lanes themselves.

Similarly, we have adaptive tech that reacts to situations by itself. Emergency braking systems are a prime example; modern cars notice objects in front of them and can brake automatically before you forget, preventing collisions.

Going even further than this, theres the idea of autonomous driving. Weve seen an example of it when talking about cruise control, but technology has become so advanced that modern cars are capable of driving themselves.

It feels like weve covered a lot in this post, but weve barely scratched the surface of how different cars were in the past compared to now. These are the main changes and improvements, and its fair to say that the modern car has evolved a lot from the turn of the century. What else can we expect from the auto industry as new innovations continue to pile on?

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The Dramatic Evolution Of Cars In The Last 20 Years - The Future of Things

In the early 1960s, Walt Disney was riding high on the success of Disneyland in California.

Disneyland had a problem though. Only a small fraction of its guests were from the East Coast of the U.S., which meant Disney was missing out on a huge potential audience for his theme park. To expand the companys reach and scope, he began looking for a location that would match his grand ambitions, and Florida, with its abundance of cheap land and warm climate was a natural choice.

On November 22, 1963coincidentally the day JFK was assassinatedWalt flew over to the Orlando to do some location scouting. At the time, most of the area was swampland, though there was one area adjacent to an under-construction highway that caught his attention.

Using shell companies to preserve his anonymity (and to keep the price down), Disney began acquiring the sprawling properties that would become todays Walt Disney World (WDW).

When Walt Disney World finally opened in 1971, it included the main Magic Kingdom site, as well as two golf courses and two hotelsContemporary Resort and the Polynesian Village Resort. These areas were all connected by a monorail system.

As these maps depict, there was a plan to develop three unique themed zones around the Seven Seas Lagoon: Persian, Asian, and Venetian.

However, these projects were scrapped after the 1973 oil crisis as tourism declined.

The original master plan for Walt Disney World did not include plans for the Seven Seas Lagoon, and it was likely added so that the displaced earth could be used to fortify swampy sections of the property to make them suitable for building.

The first major Disney World expansion was Epcot Center, which opened in 1982. The site, which was twice as big as the Magic Kingdom, is best described as a permanent worlds fair.

The park was anchored by Future World and Spaceship Earth, the iconic geodesic sphere structure that sat at the entrance of the park.

Surrounding the nearby lake were pavilions themed after various locations in the world.

Though the scope of Epcot was impressive at the time, it was still vastly scaled down from Walt Disneys original vision for a fully functioning city of the future. Ultimately, the company was uncertain about the feasibility of operating a functional city, so the idea was scrapped in favor of the current iteration.

Disney-MGM Studios opened in 1989, in a location just south of Epcot. The park featured imagined worlds from film, television, music, and theater, drawing inspiration from the Golden Age of Hollywood.

To make this happen, Disney entered into a licensing agreement with MGM to help increase the variety of film representation within the park.

Approximately 11 million visitors pass through Hollywood Studios every year.

In 1998, WDW added a fourth theme park called Animal Kingdom. Its the largest theme park in the world, covering 580 acres, and combines elements of both a zoo and theme park.

A central feature of Animal Kingdom is the massive Tree of Life. The 145 foot tall work of art contains 325 unique animal carvings and over 100,000 artificial leaves. The park itself features about 2,000 animals representing 300 species.

Around 13 million people visit the theme park each year.

So, how big is Walt Disney World today? 43 square miles, which is about the same area as San Francisco and and twice the size of Manhattan.

The scale of todays WDW has fully eclipsed the original version of the site. The resort, which featured two hotels in 1971, now has more than 20, with 30,000 hotel rooms. WDW is also the largest single site employer in the United States.

Looking at the map above, one might wonder whether this sprawling entertainment empire is bursting at the seams. Will WDW eventually build over its entire property? The answer is somewhat complicated.

While the stylized maps above do a great job of highlighting WDWs many attractions, they generally downplay an important fact. Much of the land owned by Disney is still undeveloped, and there is a lot of space between the various parks. Much of this space is earmarked as conservation areas, and only some of the remaining land is actually suitable for development. Despite the sheer size of the property occupied by WDW, space for expansion grows increasingly scarce with each new development.

The stylized maps also downplay the size of WDWs parking lots, which are extensive. The Magic Kingdom parking lot, for example, is actually larger than the theme park itself.

The giant map below is an accurate representation of the parks layout, and includes facts on some of the attributes of the park.

This enormous land parcel is also unique in that its a kind of self-governing municipality, with its own fire department and emergency services. The districtofficially known as the Reedy Creek Improvement Districtis governed by a five-person Board of Supervisors elected by the landowners in the district. As a result, high-level Disney employees essentially run the entire region encompassing WDW.

In the 50 years since the Magic Kingdom first opened its turnstiles, Disneys own kingdom in Central Florida has transformed dramatically. With Disneys continued financial success and the freedom to make large-scale moves within their property, the next 50 years will no doubt bring more dramatic changes to the worlds biggest theme park.

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The 50-Year Evolution of Walt Disney World in Maps - Visual Capitalist

Save to read list Published by Will Owen, Deputy Editor Global Mining Review, Thursday, 07 October 2021 09:15

Evolution Mining Ltd has entered into a binding agreement with Navarre Minerals Ltd to sell the Mt Carlton gold mine (includes Crush Creek) in Queensland for a total consideration of up to A$90 million.

The total consideration consists of:

Evolution has consistently stated that a key objective of its corporate strategy is to continuously seek to upgrade the quality of its portfolio through either acquisition or divestment and the sale of Mt Carlton is consistent with this strategy. Consistent with other divestments, Evolution will retain upside exposure to Mt Carlton through the shareholding in Navarre of up to 19.9% and the contingent considerations.

Navarres economic interest in Mt Carlton will commence from 1 October 2021, with the transaction expected to close in the December 2021 quarter. Evolution will be providing support to Navarre to ensure a safe and smooth transition of ownership.

Commenting on the transaction, Executive Chairman Jake Klein said:

Mt Carlton was Evolutions first development project and has generated excellent returns for shareholders since it was commissioned in 2013. With the company focussed on delivery of growth projects at the cornerstone assets in the portfolio, we believe now is the time to hand Mt Carlton over to an emerging gold producer who can focus on extending the operations mine life. The exposure we have retained will enable Evolution shareholders to benefit from the future success of the operation.

Evolution would like to thank our employees, contractors, suppliers, the traditional custodians of the land the Birriah People, and the local community for their contribution to Mt Carltons success. We are confident that Navarre will be a great partner for those stakeholders in the future.

Read the article online at: https://www.globalminingreview.com/exploration-development/07102021/evolution-mining-to-divest-mt-carlton-gold-mine-to-navarre-minerals/

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Altus Strategies Plc has announced that a 10 000 m reverse circulation and 1300 m diamond drilling programme is underway at the company's 100% owned Diba gold project in western Mali.

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Evolution Mining to divest Mt Carlton gold mine to Navarre Minerals - Global Mining Review

Frontier plans to show off the world premiere of Chaos Theory, one of the four modes in Jurassic World Evolution 2, later this week on October 8th. Chaos Theory is one of four modes available with the game, along with the campaign, and the Challenge and Sandbox modes. From what Frontier's said so far, Chaos Theory is aimed at creating a nostalgia hit. Chaos Theory "lets you play through key moments of your favourite films with a twist. Experience what-if scenarios from iconic Jurassic World and Jurassic Park films and see how these scenarios unfold when youre in charge." One example Frontier gave was The Lost World: Jurassic Park scenario, where "you're charged with building Jurassic Park: San Diego and making it a success."

Naturally, Jeff Goldblum seems to be involved with this world premiere, along with gaming personality Jesse Cox. The premiere takes place this week, on October 8th at 11am PST/7pm BST. What do you hope to see with Chaos Theory? Let us know in the comments!

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Jurassic World Evolution 2 to show world premiere of Chaos Theory later this week - TrueAchievements

When LinkedIn co-founder and Greylock partner Reid Hoffman first coined the term blitzscaling, he kept it simple: Its a concept that encourages entrepreneurs to prioritize speed over efficiency during a period of uncertainty. Years later, founders are navigating a pandemic, perhaps the most uncertain period of their lives, and Hoffman has a clarification to make.

Blitzscaling itself isnt the goal, Hoffman said during TechCrunch Disrupt 2021. Blitzscaling is being inefficient; its spending capital inefficiently and hiring inefficiently; its being uncertain about your business model; and those are not good things. Instead, he said, blitzscaling is a choice companies may have to make for a set period of time to outpace a competitor or react to a pandemic rather than a route to take from idea to IPO.

That doesnt mean startups should avoid prioritizing breakneck speed, especially in industries like fintech and edtech, where the pandemic spotlighted a lot of potential. Instead, Hoffman thinks the pandemics real impact on his definition is that the benchmark for what you may need to do in order to outpace your competitors to scale in an ecosystem may have changed.

Hoffmans broadened view of blitzscaling blends well with his firms recent announcement of a $500 million seed fund. The close came weeks after Andreessen Horowitz closed its own $400 million seed fund.

Greylock claims that its new fund is the largest pool of venture capital dedicated to backing founders at one, and explicitly said that it is willing to write large seed checks at lean-in valuations, which gives companies more runway to hit milestones without taking on additional dilution. Its fair to say that Greylocks checks could help seed-stage startups afford to blitzscale while still prioritizing runway and other business-oriented resources.

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Reid Hoffman on the evolution of 'blitzscaling' amid the pandemic - TechCrunch

Some time in Earths early history, the planet took a turn toward habitability when a group of enterprising microbes known as cyanobacteria evolved oxygenic photosynthesis the ability to turn light and water into energy, releasing oxygen in the process.

This evolutionary moment made it possible for oxygen to eventually accumulate in the atmosphere and oceans, setting off a domino effect of diversification and shaping the uniquely habitable planet we know today.

Now, MIT scientists have a precise estimate for when cyanobacteria, and oxygenic photosynthesis, first originated. Their results appear today in the Proceedings of the Royal Society B.

They developed a new gene-analyzing technique that shows that all the species of cyanobacteria living today can be traced back to a common ancestor that evolved around 2.9 billion years ago. They also found that the ancestors of cyanobacteria branched off from other bacteria around 3.4 billion years ago, with oxygenic photosynthesis likely evolving during the intervening half-billion years, during the Archean Eon.

Interestingly, this estimate places the appearance of oxygenic photosynthesis at least 400 million years before the Great Oxidation Event, a period in which the Earths atmosphere and oceans first experienced a rise in oxygen. This suggests that cyanobacteria may have evolved the ability to produce oxygen early on, but that it took a while for this oxygen to really take hold in the environment.

In evolution, things always start small, says lead author Greg Fournier, associate professor of geobiology in MITs Department of Earth, Atmospheric and Planetary Sciences. Even though theres evidence for early oxygenic photosynthesis which is the single most important and really amazing evolutionary innovation on Earth it still took hundreds of millions of years for it to take off.

Fourniers MIT co-authors include Kelsey Moore, Luiz Thiberio Rangel, Jack Payette, Lily Momper, and Tanja Bosak.

Slow fuse, or wildfire?

Estimates for the origin of oxygenic photosynthesis vary widely, along with the methods to trace its evolution.

For instance, scientists can use geochemical tools to look for traces of oxidized elements in ancient rocks. These methods have found hints that oxygen was present as early as 3.5 billion years ago a sign that oxygenic photosynthesis may have been the source, although other sources are also possible.

Researchers have also used molecular clock dating, which uses the genetic sequences of microbes today to trace back changes in genes through evolutionary history. Based on these sequences, researchers then use models to estimate the rate at which genetic changes occur, to trace when groups of organisms first evolved. But molecular clock dating is limited by the quality of ancient fossils, and the chosen rate model, which can produce different age estimates, depending on the rate that is assumed.

Fournier says different age estimates can imply conflicting evolutionary narratives. For instance, some analyses suggest oxygenic photosynthesis evolved very early on and progressed like a slow fuse, while others indicate it appeared much later and then took off like wildfire to trigger the Great Oxidation Event and the accumulation of oxygen in the biosphere.

In order for us to understand the history of habitability on Earth, its important for us to distinguish between these hypotheses, he says.

Horizontal genes

To precisely date the origin of cyanobacteria and oxygenic photosynthesis, Fournier and his colleagues paired molecular clock dating with horizontal gene transfer an independent method that doesnt rely entirely on fossils or rate assumptions.

Normally, an organism inherits a gene vertically, when it is passed down from the organisms parent. In rare instances, a gene can also jump from one species to another, distantly related species. For instance, one cell may eat another, and in the process incorporate some new genes into its genome.

When such a horizontal gene transfer history is found, its clear that the group of organisms that acquired the gene is evolutionarily younger than the group from which the gene originated. Fournier reasoned that such instances could be used to determine the relative ages between certain bacterial groups. The ages for these groups could then be compared with the ages that various molecular clock models predict. The model that comes closest would likely be the most accurate, and could then be used to precisely estimate the age of other bacterial species specifically, cyanobacteria.

Following this reasoning, the team looked for instances of horizontal gene transfer across the genomes of thousands of bacterial species, including cyanobacteria. They also used new cultures of modern cyanobacteria taken by Bosak and Moore, to more precisely use fossil cyanobacteria as calibrations. In the end, they identified 34 clear instances of horizontal gene transfer. They then found that one out of six molecular clock models consistently matched the relative ages identified in the teams horizontal gene transfer analysis.

Fournier ran this model to estimate the age of the crown group of cyanobacteria, which encompasses all the species living today and known to exhibit oxygenic photosynthesis. They found that, during the Archean eon, the crown group originated around 2.9 billion years ago, while cyanobacteria as a whole branched off from other bacteria around 3.4 billion years ago. This strongly suggests that oxygenic photosynthesis was already happening 500 million years before the Great Oxidation Event (GOE), and that cyanobacteria were producing oxygen for quite a long time before it accumulated in the atmosphere.

The analysis also revealed that, shortly before the GOE, around 2.4 billion years ago, cyanobacteria experienced a burst of diversification. This implies that a rapid expansion of cyanobacteria may have tipped the Earth into the GOE and launched oxygen into the atmosphere.

This new paper sheds essential new light on Earths oxygenation history by bridging, in novel ways, the fossil record with genomic data, including horizontal gene transfers, says Timothy Lyons, professor of biogeochemistry at the University of California at Riverside. The results speak to the beginnings of biological oxygen production and its ecological significance, in ways that provide vital constraints on the patterns and controls on the earliest oxygenation of the oceans and later accumulations in the atmosphere.

Fournier plans to apply horizontal gene transfer beyond cyanobacteria to pin down the origins of other elusive species.

This work shows that molecular clocks incorporating horizontal gene transfers (HGTs) promise to reliably provide the ages of groups across the entire tree of life, even for ancient microbes that have left no fossil record something that was previously impossible, Fournier says.

This research was supported, in part, by the Simons Foundation and the National Science Foundation.

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Zeroing in on the origins of Earth's single most important evolutionary innovation - MIT News

October 1, 2021

In a story that took the world by storm, a downtrodden yet cunning lower-class family infiltrates a wealthier neighborhoods home. Then all hell breaks loose.

If this sounds like the setup of 2019s Academy Award-winning film sensation Parasite, youd be right. But it could also pass as a plot driver for one of the most diverse animal groups on earth: ants. Diversity of life history traits in the formicine ants: (A) Members of the F. fusca group practicing independent colony foundation; (B) F. obscuripes, representing the F. integra group (Nearctic members of the paraphyletic rufa group), which practices dependent and temporary social parasitic colony founding; (C) F. gynocrates, representing the facultatively dulotic species of the F. sanguinea group, with a worker of its neogagates group host species, F. vinculans; (D) the highly modified worker of Polyergus mexicanus, representing the obligately dulotic formicine ants in the genera Polyergus and Rossomyrmex. All images courtesy of Alex Wild (www.alexanderwild.com) Download Full Image

Christian Rabeling, Arizona State University researcher and associate professor of organismal evolutionary biology, can now tell a story 30 million years in the making, of a myrmecological marvel, the evolution of social parasitism in ants.

He and his team, including colleague and former postdoctoral researcher Marek L. Borowiec, now assistant professor at the University of Idaho, and long-term friend and colleague Stefan P. Cover, safekeeper of the worlds largest ant collection at the Museum of Comparative Zoology at Harvard University, have now revealed the latest plot twists to understanding the origins and evolution of ant social parasitism.

Identifying the conditions associated with ant life history and their transition from cooperative colony life to exploitative social parasitism is important for understanding how changes in behavior contribute to speciation, said Rabeling, a professor in ASUs School of Life Sciences and a core researcher in the universities social insect group.

Rabeling is fascinated by social parasitism,first studyingthis behaviorin leaf-cutter antsand now, in his latest study, one of the most diverse groups of all: Formica ants.

So, the first question was, how did Formica ants evolve? No one had done a detailed phylogenetic analysis that looked into that, Rabeling said.

Christian Rabeling

First, a group of Formica ants lost their ability to form the hub of ant life colony formation independently. Once this ability was loss, a shift to two other more complex types of social parasitic behaviors took place.

Here, we demonstrate that social parasites evolved from an ancestor that lost the ability to establish new colonies independently, and that highly specialized parasites can evolve from less complex social parasite syndromes, Rabeling said.

And like most successful Hollywood movies, once a successful formula was proven, Rabeling found this same ant plotline was repeatedly borrowed, again and again.

Social parasitism is a life history strategy that evolved at least 60 times in ants, and more than 400 socially parasitic species are known from six distantly related subfamilies, Rabeling said.

The study appears in the online edition of the Proceedings of the National Academy of Sciences.

Among the 14,000 different ant species to study, Rabeling chose one of the largest and most diverse groups of ants, Formica ants. There are 172 species within this supergroup (or genus), with half exhibiting social parasitic behavior, making it one of the largest on Earth.

Their first step to seeing a bigger picture of Formica social parasites was to make a global evolutionary tree to better understand the historical relationships between the species, and a window into how different species became social parasites.

To make a Formica evolutionary tree, or phylogeny, scientists look at the DNA level to make branching relationships between the Formica ant species and an understanding of the inheritance of traits that control social behavior and diversity.

To do so, Rabelings team collected DNA samples from 101 Formica species (representing all 10 known species groups) across a global geographic distribution and carefully calibrated these data across evolutionary time.

Rabelings team collected DNA samples from 101 Formica species across a global geographic distribution and carefully calibrated these data across evolutionary time. This ant supergroup was one of the most successful in the history of life, first originating in the Old World around 30 million years ago and dispersing multiple times to the New World and back.

They showed this supergroup was one of the most successful in the history of animal life, first originating in the Old World around 30 million years ago and dispersing multiple times to the New World and back as land bridges came and went.

From their analysis, they found that Formica last shared a common ancestor with its sister group, Iberoformica, around 33 million years ago and likely originated in Eurasia during the Oligocene era, after a long global cooling period.

The hub of ant life is the colony. Beneath the mound of a typical ant hill is a netherworld that can extend several feet deep underground in an intricate ant subway system of tubes and tunnels.

Ants are also very adaptable. They can live in trees, under boulders or entirely underground, sans hill.

The typical colony consists of one or moreegg-laying queens, numerous sterile females (workers, soldiers) and, often seasonally, many winged sexual males and females. Colonies can differ in size, from rural to mega city-sized. For example, in the speciesF. fusca,colonies are found with only 500 workers, while the F. yessensisspecies has mammoth colony sizes of 300 million workers.

Ants exhibit all sorts of social behavior that often make for apt allusions to people. Some are good: living peacefully in colonies, cooperating to find food, caring for their young and defending the nest against rival species. But others have become bad actors: raiding rival nests, zombifying other worker ants and enforcing a caste system to benefit the monarchy of an all-too-dominant queen.

There are three major classes of social parasites in ants that serve to exploit the host colony for their own gain: 1) temporary, 2) dulotic (pirate ants who steal the worker brood of other nests) and 3) permanent social parasitism.

We were looking for an ant group where we could find all three life histories, and we found it with Formica ants, Rabeling said.

And when they carefully annotated all of the life history data for each Formica species in a gigantic table, and lined that up with the DNA timeline of when the species first split and made new evolutionary branches from each, an important pattern began to materialize: the three major classes of social parasites evolved at distinct, yet clearly separate timepoints.

This was a moment of clarity, Rabeling said. "Its like you have all these different mosaic pieces. You place one stone here, another stone there and then theres a new observation that adds yet another piece to the mosaic. But once you put in the evolutionary time context, all of sudden, you can see the entire picture. Its deeply satisfying.

This picture shows the evolution of queen miniaturization in temporary social parasitic Formica ants.

Rabeling showed that temporary social parasitism evolved first, around 18 million years ago. The first key step in this process is that the queens somehow lose the ability to form colonies on their own.

So, the queens of temporary socially parasitic ant species invade the host nest, kill the resident queen(s), and the host workers raise the parasitic queens offspring. In the absence of an egg-laying host queen, the host workforce is gradually replaced until the colony is composed solely of the temporary social parasite species.

Interestingly, evolutionary reversals from social parasitism to independent colony founding were not recovered, suggesting that a transition to a socially parasitic lifestyle is irreversible, Rabeling said.

After this main event, more recent branches (or clades) of socially parasitic species have secondarily transitioned to the other parasitic life histories, dulotic and permanent social parasitism.

In the second example, the queens of dulotic social parasites start their colony life cycle as temporary social parasites, and once sufficient parasitic workers have been reared, they conduct well-organized raids of nearby host nests to capture their brood. Some brood are eaten, but most workers hatch within the parasites nest and contribute to the workforce of the colony.

They think they are right at home, so they dont even recognize that they are in a different species nest, Rabeling said.

Rabelings team found that dulotic behavior evolved once some time prior to approximately 14 million years ago much later than temporary parasites. Therefore, dulotic behavior and temporary social parasitism did not evolve simultaneously in Formica, but instead dulosis evolved secondarily from a temporary socially parasitic ancestor.

The single origin of dulotic behavior in a diverse clade of temporary social parasite species supports the hypothesis that dulosis originates only under rare circumstances, Rabeling said. Rabeling notes that even Charles Darwin threw his hands up in the air when trying to explain one species of dulotic ant in his On the Origin of the Species book.

A sketch of a Formica ant by Charles Darwin.

By what steps the instinct of F. sanguinea originated I will not pretend to conjecture, Darwin wrote.

Rabeling marvels at this history: Its really beautiful that you can trace the ant question all the way back to the 'Origin of Species.'

Since that time, three not entirely mutually exclusive hypotheses have been proposed to explain the origins of this highly specialized behavior: 1) predation, 2) brood transport and 3) territorial competition.

Our phylogenetic results and behavioral observations indicate that the predatory behavior of temporary social parasites could lead to the evolution of facultative dulosis in Formica, Rabeling said.

Finally, in the last example, most permanent social parasite (i.e., inquiline) speciesare tolerant of the host queen, allowing her to continuously produce host workers, whereas the inquiline queens focus their reproductive effort on sexual offspring.

Rabeling explains the complex behavior as follows: In this particular situation, you have a queen that behaves parasitically, and the queen that behaves socially. And for reason we dont understand, the two do not integrate. So, even though they exist in the same nest, they live parallel but separate lives and end up forming two species: the host and the inquiline social parasite. This is an intriguing example of how two species evolve in direct sympatry, and their different life histories is one important factor why they do not interbreed.

Inquilines obligately depend on their hosts, and most inquiline species lost their worker caste entirely.

The only confirmed workerless inquiline social parasite in the genus Formica is F.talbotae. However, F. talbotae is special because it does not live peacefully together with a host queen inside the host colony. It seems to specifically target host colonies that have lost their queens. This is an extremely specialized lifestyle that is only known from a couple of other ant species.

Formica talbotae is phylogenetically nested within the difficilis clade, suggesting that worker-less permanent parasitism evolved once from an ancestor practicing temporary social parasitism, Rabeling said. To our knowledge this is the first empirical evidence for an evolutionary transition from temporary to workerless inquiline social parasitism.

For, on the evolutionary route of social parasite evolution, highly similar plots for the parasitic life history syndromes across all eusocial insects can lead to a new best picture emerging.

Our findings emphasize that social parasite syndromes readily originate in socially polymorphic organisms and evolved convergently across the ant phylogeny, Rabeling said.

They conclude that in the formicine genera Formica, Polyergus and Rossomyrmex, dulotic or brood-stealing social parasitism originated repeatedly and convergently. In the genus Formica, multiple transitions to increasingly more complex socially parasitic life histories evolved.

Finally, the permanent social parasites, F. reflexa and the workerless F. talbotae, evolved independently from temporary social parasitic ancestors. Rabeling hopes this knowledge will spur others to make new discoveries.

Our study outlines the life history changes associated with the transition from a cooperative eusocial to exploitative socially parasitic life history, Rabeling said. Given the high diversity of social parasite species in the genus Formica, and considering the high degree of morphological and behavioral specialization, socially parasitic Formica species appear to be an ideally suited study organism for investigating caste determination and for exploring the genetic basis underlying behavioral and life history evolution.

These ant observations, gained from extensive fieldwork and studying the life history of individual species behaviors, have informed the scientific community for decades. But now, with scientific technological progress and access to low-cost DNA sequencing, for the first time, it has opened up an exciting new vista to make it possible to better link ant behavior to genes and molecules that may be playing a role behind the scenes.

For us, this is a fantastic period right now, Rabeling said. Just the ability to ask these questions was probably the most exciting part of this study.

The opportunity to produce a more holistic picture of social behavioral evolution propels and thrills Rabeling.

It has been a prime motivation for Rabeling, who once did his postdoctoral studies with famed sociobiologist E.O. Wilson. And since coming to ASU five years ago, he will continue to specialize in understanding the underpinnings of parasitic ant behavior.

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Scientists discover a host of reasons for the evolution of social parasites in ants - ASU Now

The COVID-19 pandemic has changed the way the world works, which has made planning for the future a question of vital importance. In this episode of the McKinsey on Government podcast, Susan Lund, a McKinsey partner and a leader of the McKinsey Global Institute, discusses the changes brought about in the pandemic, which of these changes might stick around, and how the workforce will need to evolve in the postpandemic landscape.

Audio

Francis Rose: Welcome to McKinsey on Government. Every episode examines one of the hardest problems facing government today, and solutions from McKinsey experts and other leaders. Im the host of McKinsey on Government, Francis Rose. The economic impact of the pandemic is slowing. The stock market is going up. Unemployment is going down. This has economists and government leaders thinking about how the postpandemic economy will work.

Thats the subject of McKinsey on Government this week with Susan Lund, partner with McKinsey and a leader of the McKinsey Global Institute. Susan, welcome. Thanks very much for coming on the program. What patterns do you see in the way that people want to work, the way people want to spend, and the way people want to consume and deliver services as a result of what weve been through over the past 18 months, and where it appears were headed, say, over the next 18 months?

Susan Lund: Well, there are three big groups of trends that we think the pandemic accelerated and that are going to persist at varying degrees at an accelerated rate compared to what we thought a year and a half ago. I think that if this pandemic had lasted just two or three months, we wouldve gotten through it and all gone back to business as usual.

But the fact that weve been here now working from home and operating in different ways for the last 14 or 15 months, weve all learned new behaviors, and weve found some silver linings. The first group of changes has to do with how companies adopted technology.

Usually in a recession, companies cut back on capital expenditures. They hold onto cash while they wait to see what demand does and when the economy recovers. But in this pandemic, technology was one of the key ways that companies kept operations going. We saw an uptick in adoption of everything from automation and robotics, to virtual chatbots issuing customer refunds, to service robots delivering supplies in hospitals, to virtual-reality headsets enabling technicians to repair very complicated machinery remotely.

From here on, we think that technology adoption will just continue, but from this new, higher level. So this is something that had been happening. We foresaw that work would change and skills would change. But the pandemic has really sped up that adoption of technology.

The second big group of changes, of course, is remote work. Before the pandemic, only 5 to 6 percent of Americans regularly telecommuted for their jobs. During the pandemic, up to about 35 to 40 percent of people were working from home. Now, in many cases, weve learned that not everything weve done working from home was as productive. I think if you ask most teachers and parents, they would agree that online schooling for young children really didnt work out so well. So when schools reopen and were all vaccinated, we think that working from home will drop away.

But in many office settings, weve found some silver linings to remote work. Employees like giving up the commute time. There was less hierarchy and faster decision making. Many companies said that the relationships between field offices and headquarters or international offices and headquarters is stronger because everyone was on a level playing field on their cameras. And companies adopted new types of technology to enable virtual collaboration that has actually increased efficiency.

So for all these reasons, we think that some types of hybrid remote work are probably here to stay. At the same time, the flip side is that some business travel may not come back, because weve learned that virtual meetings, in some instances, can replace what we used to get on an airplane and travel for.

The third big set of changes has to do with consumers and digital or virtual transactions. Whether it was online banking, e-commerce, digital payments, telemedicine, or grocery delivery, all types of consumer digital transactions took off because there was really no alternative. A lot of users of these digital channels that hadnt tried it before were forced to. Now that they have, our consumer pulse surveys indicate that they find them efficient and convenient. They say theyre going to continue operating in these new ways to some degree after the pandemic.

Francis Rose: I want to walk through each of those three items and think about them through the lens of the federal government in particular, as well as regarding governments broadly. The first, the technology adoption, it strikes me. Every single executive that I talk to in the government from March of last year through this moment has said we are taking this as an opportunity to accelerate what we were already doing in the technology adoption and technology modernization refresh cycle. Is that what youre seeing more broadly across the economy? Or is there some other opportunity that maybe people in government havent seen yet and might be missing out on, Susan?

Susan Lund: Mostly, it is an acceleration of existing technology and digitization plans. I know for government services, online transactions and e-government are areas of investment. Another area is what we call robotic process automation, where you take paperwork processes, for instance, that put together financial reports that draw data from several sources. This can be automated.

So with all of these things, the silver lining could mean that the economy could see higher productivity growth, not just in government but more broadly in the three to five years to come. And that would be very welcome because we need to remind ourselves that before the pandemic, and for the last ten years, productivity growth in the United States and in other advanced economies was actually low and falling.

Francis Rose: I guess the thing that people are thinking aboutnot just the technologists in government but the practitioners, the frontline managers are thinking it: What sticks? And what sticks relates to the other two items that you lay out here. What are we going to do about remote work? And what are we going to do about the way that we interface with the citizens, customerswhatever word you want to use to meet the mission of our agencyto meet the mission of our organization?

The remote-work element that I scribbled down as you were talking about ittheres a bunch of them, but the one that jumped out at me is the faster decision-making process. Whats facilitated that? And what is the implication of the faster decision-making process, do you think, for organizations moving forward? Is that something that will even stick in what people perceive, at least, to be a more bureaucratic environment, like a government agency, as opposed to a private-sector company or an academic institution?

Susan Lund: We hope that it will stick. It really has to do with agile ways of working. One of the reasons I think that decision making sped up is simply because people arent traveling as much. It was easier to get people around a Zoom, look each other in the eye, and make decisions. One CEO said, Ive learned to limit the number of people on a Zoom call. On his particular screen, he could see 12 at once. And he said no meeting is going to have more than 12 people. Lets figure out who really needs to be part of this decision.

It goes to this broader concept of agile ways of working that companies have been adopting. The idea there is to put together teams of people working across boundaries to try what we call the minimum viable product, and then to iterate, to learn fast. This has all been enabled by virtual meetings because you dont have to connect people walking between different buildings or traveling to different locations. Its simply made the ability to meet and make decisions much faster. Thats something that we would hope would continue.

I think that many companies have found that we dont need all those layers of decision making that we thought we needed or the five-month or two-year approval process for an IT project. In the early days of the pandemic, we just did it because we had to, and that worked out well. Its really been an unlock, I think, for many executives in realizing that you can move a lot faster than you thought you could and still get to quality outcomes.

Francis Rose: From a risk-management perspective, a lot of those decisions, whether they were human-capital decisions or whether they were IT decisionsthe ones that didnt work out as well still werent horrible. Is that a fair representation?

Susan Lund: It is. I think that what most organizations have learned over the past 14 months is to move quickly but also to adjust course often. See how it works. Of course, we had a changing external condition regarding the ability to go to an office or travel. We had to deal with the external environment. But this really reinforced the notion that weve got to be nimble. We need to listen actively and then adjust course quickly when needed.

I think that in 2021 and into 2022, since now organizations are thinking about a return to the office and what types of flexible work will be possible going forward, theyre going to need to take that same pilot and experimentation approach. Im often asked which companies are doing this best. Who are the leaders? And I say, Unfortunately, there are none. Everybody is figuring this out together.

The most successful organizations will be the ones that try something and set a policy, because employees certainly want to know what the expectation is going forward. Whether its three or four days a week in the office or full time in the office, or some people can continue to work remotely on a permanent basis, employees are craving information about what to expect over the next few months. But beyond that, everybody has to realize were cocreating this together. And were going to try some things. If we find out that there are pitfalls and it doesnt work, then well adjust course as needed.

Francis Rose: If we take that description that you just gave and extrapolate it over an entire enterpriseto make fast decisions and adjust course quicklythats almost the textbook definition of resilience, too, which is what every organization is aspiring to, especially in an environment like weve seen over the past 15 months.

Susan Lund: Thats right. The interesting thing for manufacturing companies and supply chains is that COVID-19 was only the first shock. Then we had a freak Texas deep freeze that disrupted the plastics industry. We have a global semiconductor shortage. We had a massive container ship get stuck in the Suez Canal. The disruptions and the shocks just keep coming. And you cant try to predict these black-swan events. The next big global disruption will likely not be a pandemic. It will be something different. But the ability to adjust very quickly and react nimbly is what differentiates.

Francis Rose: I also scribbled down a note about the comment you made about business travel when it came to remote work, about whether that will come back or not. And I wonder what that means in the private sectorbut especially, obviously, in the government spaceabout the ability of people and organizations to collaborate in person moving forward.

I recall that a number of years ago, there was a conference freeze. Nobody could go to any conferences for a period of time. It was especially profoundly difficult for the scientific community in the federal government. Do you expect at some point in time that people will say, as they did after thatessentially, a complete shutdown like we saw as a result of the pandemicNo, no. Theres some middle ground here. And some of this has to come back. Or do you think a lot of this is going to go virtual moving forward, and there will just be almost a zero level like were seeing now?

I think that many businesspeoplewho traveled, or government peoplewho traveled, will look back andrealize there was some of what I call low-value travel.

Susan Lund: Well, my crystal ball is broken at the moment. But I would say that I think conferences will come back. I think that innovation and collaboration, negotiations between parties, learning eventsthese are the types of things where you really do benefit from being across a table from someone, looking in their eyes, reading their body language, having the little conversations in and out of the room, the chance encounters with someone where you learn a new idea that you werent expecting. These are the things that we cant schedule in a Zoom meeting.

Those are the activitiesas people go back to the office, this is what people should be and will be doing in the office. If youre going to an office and sitting alone at a desk on your computer all day, that can be done from anywhere. But its really that collaboration. So I dont think the future of business conferences is dead. I do think we will go back.

But, in reflection, I think that many businesspeople who traveled, or government people who traveled, will look back and realize there was some of what I call low-value travel. You went to meetings that really werent that important or could have easily been done virtually. So its certainly not to say were not going to conferences, or were not going to meet customers or suppliers in person. Those things are really important. And I think, more than ever, many of us or most of us are really craving those in-person interactions again. Well find it very energizing. But on the margins, people were traveling at the drop of a hat. And those are the types of things that I think many companies are thinking theyll cut back on some.

Francis Rose: You mentioned something there, Susan. And I dont even think it was intentional on your part. But it jogged something in my mind regarding remote work. One of the issues that a lot of human-capital people in government are telling me theyre struggling with is kind of the second phase of onboarding, which [happens after] a new employee has been with the organization for a period of time. They kind of have their sea legs underneath them.

But theres not a watercooler opportunity. Theres not the walking-down-the-hallway check on you. Susan, youve been here for two weeks. Hows everything going? Youve been here for a month. Hows everything going? Or the call into the office just for a five-minute checkup. Those kinds of things are not happening as much, except where organizations are superconscious of it and superdeliberate about it. Is that just something people are going to have to get used to doingbeing superdeliberate about it? Or is that something that maybe you think organizations should rethinkthe way that they interact with those people and help train those people up?

Susan Lund: Yeah, well, I think that onboarding and training and mentoring younger, more junior colleagues are some of the reasons we will go back to the office, because those things happen in person. Its great for professionals like myself whove been at my company for more than 20 years. I have a vast network.

But its very different for people who are newer to the organization who want to build new relationships but who also want to have that coaching and real-time mentoring. The quick comments like, Good job on that presentation, or, You answered that question really well, or, You couldve thought about x, y, zthose sort of little interactions, microinteractions that happen when youre working together that dont happen over Zoom. So I do empathize with newer employees, and particularly those who joined during the pandemic who havent had that experience of getting to know their colleagues in the office yet.

Francis Rose: The third item that you laid out at the beginning of this conversation, Susan, was the way that consumers want to do business with organizations. This is the area where my sense, at least, is the federal government is still catching up with the trajectory of the pandemic. And a lot of it has to do with technology adoption we talked about in your first point, where I think a lot of government organizations started behind private sector and academia.

Is there any secret sauce to catching up in that trajectoryto providing this equivalence that if Im going to do business with the government, it works the same way as it does to do business with my bank? Or is this just a matter of the government having toI dont mean it in a pedestrian waygo through the motions? Is it that theyre just going to have to take step, step, step, step, step and get there when they get there?

Susan Lund: There have been big investments in digital delivery of government services for a long time. But increasingly, it is what suppliers and citizens and individuals want. They want things easy, quick, seamless, flawless, on demand, whenever they want to interact, whether its on a weekend or late at night, not constrained by office hours.

And so there are new opportunities now, of course, with cloud to build out better digital channels. I think for every agency, its going to take on a different flavor of what the next horizon will be. But increasingly, this is how people want to operate. It can lead to a lot of operational efficiencies. And, obviously, interacting digitally also generates a wealth of data, so you can get to know your customers and your suppliers much better and actually start to use data analysis to track patterns of behavior and what they want and anticipate what those interactions will be, rather than just being reactive.

Francis Rose: I think that concept, though, is far newer for the federal government than it is for the private sector. The private sector has understood, I think, for decades the value of being able to anticipate customer needs. I think the federal government has understood it. I think their access to the tools and data to be able to leverage that has been more of a challenge. Is there any way to shorten that curve? Or is that curve also just going to happen at whatever pace an agency is able to drive it?

Susan Lund: Well, look, its always faster to be the follower than the innovator. So now that Netflix knows exactly which TV shows and movies to recommend to me, right, the AI [artificial intelligence] algorithms are there. Now how do we apply that to various federal agencies? I think that there should be opportunities to leapfrog ahead, particularly in use of big data and AI algorithms, now that many different private-sector players have shown how to build those, train the algorithms, and implement them.

Francis Rose: Something else I think organizations are figuring out now is how all of these changes, all three of these changes and other things that organizations are dealing with, will impact what they need out of their workforces, the skills that they will want their people to have moving forward. Is there a dramatic difference in your view, Susan, in what the workforce skill set is today broadly versus what it will be, say, two years from now or five years from now?

Susan Lund: Yeah. I think that the summation of the trends we just talked about will spur a faster evolution of the jobs that are in demand in the economy and the skills that people need to fill them. So, economy-wide, we may see declines in demand for a lot of low-skill service jobsfor instance, in food service, retail cashiers, customer service agents in banks or hotelsgiven all this digital adoption and everything we just talked about.

And that will create policy challenges. How do we make sure that people currently in those jobs have opportunities to pursue training programs or short-term credential programs to get jobs that are in demand? Because there are many jobs in demand. The healthcare sector is booming. We have a nursing shortage already thats been amplified by the pandemic. We need more people with digital skills and IT skills to maintain and run the technology.

So theres lots of demand for work. But the shifts in the mix of occupations in the economy could be much larger than we foresaw before the pandemic, and its increasingly skewed toward jobs that require specific skills. That will be a challenge for federal policy and state policy to rethink education and training programs for the workforce and for individual government agencies and organizations to think about their own workforce. How are they going to reskill or upskill their current workforce to enable them to succeed in what will be needed in the next three to five years?

Francis Rose: The federal government has already undertaken a couple of reskilling and upskilling initiatives. The Office of Management Budget drove that within the last year and a half or so. Theres a cyber-reskilling academy. Theres a coding-reskilling academy and those kinds of things.

The challenge there is scale. I think the first cohort in the cyber-reskilling academy was in the mid to low double digits, when there are thousands, at least, of potential jobs just across the enterprise of the federal government. Forget the rest of the economy. What are the potential opportunities for scaling those kinds of reskilling? Is there something out there beyond each organization just depending on itself to be able to improve the skills of the people that work for it?

Susan Lund: Yes. I think that there are opportunities both within organizations and within working with colleges and universities and community colleges. So, on the former, we have companies with tens of thousands of employees across the United States who have expanded academies like the cyberacademy to encompass many more. Many companies are finding now that through reskilling, they can fill 50 percent or more of open positions internally. So thats a benchmark you can aim for.

Francis Rose: Were starting to run out of time, Susan. Its a great conversation. What are the potential mistakes that you could see leaders making as they try to anticipate or execute on the postpandemic economy? What could somebody really goof up if they dont stop and think about it?

Susan Lund: Well, I think that all organizations, as we talked about, are going to need to be nimble, test, listen to your workforce, listen to employees, see whats working and whats not, and then adjust course as necessary. Also understand theres not going to be a one-size-fits-all solution for large organizations.

What were finding is that companies will set an overall policy about the expectation of amount of time in the office versus flexible time elsewhere, but it will be up to individual departments and teams to figure out exactly what cadence of interaction and collaboration together makes sense for them. I think that from a broader government perspective, it would be a big mistake if we dont seriously start to invest more in modernizing some of the workforce training programs that already exist and in what education models of the future should look like.

Every great technological revolution in the pastwhen we transition from agriculture to manufacturingthats the moment that more Americans started completing secondary school or high school. And then in the transition from manufacturing to a knowledge economy, it coincided with the GI Bill after World War II. Then youve got more people going on to college and getting a tertiary degree. Were going to need, I think, an equivalent step-up in how we think about education and training to meet the demands that will be coming in the next five to ten years with the current AI and digital revolution.

Francis Rose: Does that mean an extra thing, the way that we added college onto high school 50 or 60 years ago? Or does it mean a different thing?

Susan Lund: Probably both. Certainly, its not the case that everybody needs to go to college or even needs a two-year associates degree at a community college. I think that we need a lot more creativity and flexibility about short-term credentials that people can earn.

We also need a way to recognize skills that people have learned on the job. After youve been in the workforce five or ten years, youve accumulated many different skills. But we dont have a way for people to easily demonstrate this in a way that other employers might understand.

Weve got amazing human capital and experience out there. There are some new innovations around how we recognize this and open opportunities for people to show what theyve learned on the job. And thats an exciting and promising area, for instance, that could be the equivalent of this step-up in how we think about workforce skills and human capital.

Francis Rose: What do you think is within the realm of government policy makers to establish that framework? And what would maybe not be advantageous for those policy makers to try to build? Or is that maybe not part of the discussion right now?

Susan Lund: I think policy makers can do a lot to promote innovations and race-to-the-top, race-for-the-top-type programs. Theres also funding at every level of government already for workforce development, so making sure that that goes to a wider variety of programs.

Francis Rose: Susan Lund, thanks very much for the conversation. I really appreciate it, and Ive enjoyed it immensely. Thanks for your time today.

Susan Lund: Thank you.

Francis Rose: Youve been listening to McKinsey on Government, a presentation of McKinsey. Our next episode is in a couple of weeks. You can subscribe to get McKinsey on Government everywhere you get your shows. Im the host of McKinsey on Government, Francis Rose. Thanks very much for listening.

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Evolution and opportunity in the postpandemic economy - McKinsey

Significance

Tropical moist forests harbor much of the worlds biodiversity, but this diversity is not evenly distributed globally, with tropical moist forests in the Neotropics and Indomalaya generally exhibiting much greater diversity than in the Afrotropics. Here, we assess the ubiquity of this pantropical diversity disparity (PDD) using the present-day distributions of over 150,000 species of plants and animals, and we compare these distributions with a spatial model of diversification combined with reconstructions of plate tectonics, temperature, and aridity. Our study demonstrates that differences in paleoenvironmental dynamics between continents, including mountain building, aridification, and global temperature fluxes, can explain the PDD by shaping spatial and temporal patterns of species origination and extinction, providing a close match to observed distributions of plants and animals.

Far from a uniform band, the biodiversity found across Earths tropical moist forests varies widely between the high diversity of the Neotropics and Indomalaya and the relatively lower diversity of the Afrotropics. Explanations for this variation across different regions, the pantropical diversity disparity (PDD), remain contentious, due to difficulty teasing apart the effects of contemporary climate and paleoenvironmental history. Here, we assess the ubiquity of the PDD in over 150,000 species of terrestrial plants and vertebrates and investigate the relationship between the present-day climate and patterns of species richness. We then investigate the consequences of paleoenvironmental dynamics on the emergence of biodiversity gradients using a spatially explicit model of diversification coupled with paleoenvironmental and plate tectonic reconstructions. Contemporary climate is insufficient in explaining the PDD; instead, a simple model of diversification and temperature niche evolution coupled with paleoaridity constraints is successful in reproducing the variation in species richness and phylogenetic diversity seen repeatedly among plant and animal taxa, suggesting a prevalent role of paleoenvironmental dynamics in combination with niche conservatism. The model indicates that high biodiversity in Neotropical and Indomalayan moist forests is driven by complex macroevolutionary dynamics associated with mountain uplift. In contrast, lower diversity in Afrotropical forests is associated with lower speciation rates and higher extinction rates driven by sustained aridification over the Cenozoic. Our analyses provide a mechanistic understanding of the emergence of uneven diversity in tropical moist forests across 110 Ma of Earths history, highlighting the importance of deep-time paleoenvironmental legacies in determining biodiversity patterns.

Tropical and subtropical moist broadleaf forests, including evergreen tropical rain forests and wet seasonal forests (hereafter tropical moist forests), are the most species-rich terrestrial biome on the planet (13) and are most broadly distributed throughout the Amazon basin and Atlantic forest in the Neotropics, the Congo basin and Rift Mountains in the Afrotropics, and both mainland and archipelagic South and Southeast Asia in Indomalaya (4). While all three major tropical moist forest regions (hereafter Neotropics, Afrotropics, and Indomalaya) have an exceptionally high species diversity of plants and animals in comparison with other biomes, the total regional diversity (-diversity) and number of species that coexist locally (-diversity) vary dramatically across continents (2). Specifically, moist forests in the Afrotropics typically harbor lower species diversity than the Neotropics and Indomalaya (59), leading the Afrotropics to be labeled as the odd man out (9). We refer to this phenomenon as pantropical diversity disparity (PDD). This pattern has been highlighted in several keystone taxa, such as palms (family Arecaceae), whichof roughly 2,500 species globallyhave 1,200 species in Indomalaya and 800 species in the Neotropics but only 66 species in the Afrotropics (excluding Madagascar) (10, 11). Investigating the drivers of variation in species diversity in moist forests across continents could provide an alternative perspective for understanding the processes that have shaped extraordinary tropical diversity.

Explanations for the PDD have been expressed in terms of both contemporary differences in carrying capacities between regions based on the distribution of key environmental variables (9, 12, 13) and historical differences in paleoenvironmental dynamics shaping the past distribution of tropical biomes (1419) and patterns of diversification (2022). Species diversity in tropical moist forests may be driven by contemporary climate conditions if energy and resource availability from high precipitation, temperature, and solar radiation facilitates a greater number of coexisting species (2, 23). These environmental features have been shown to explain significant variation in species diversity along a terrestrial latitudinal gradient (24), yet they also vary longitudinally between tropical regions (2) with, for example, the Afrotropics lacking analogous sites of aseasonal high precipitation found in the Neotropics and Indomalaya, which are among the most biodiverse in these regions (12). Tropical biomes in different regions also have had dramatically different paleoenvironmental histories, associated with distinct geological and climatic dynamics (2, 9, 14, 25), which may have driven variation in speciation, extinction, and dispersal rates between regions owing to dynamic patterns of fragmentation, connectivity, and habitat heterogeneity (25, 26). For example, previous paleoenvironmental reconstructions indicate that while moist forests in the Neotropics and Indomalaya have remained relatively constant in size since the Eocene, moist forests in the Afrotropics suffered a drastic reduction in area from the Miocene onward (14, 20), which is believed to have driven widespread extinction from range contractions (25, 27). Additionally, Afrotropical moist forests lay at the center of the African tectonic plate and therefore, lack the intersection of active orogeny at plate boundaries with terrestrial mesic equatorial habitat as seen in the Neotropical and Indomalayan regions, leading to the formation of the Andes in the Neotropics and the Himalayan and southwest Chinese mountain chains, as well as the Southeast Asian archipelago in Indomalaya (2, 15). Active orogeny has presented dynamic opportunities for ecological and allopatric speciation (19, 28, 29) and may explain the disparity in biodiversity among tropical regions.

Drawing inferences about historical processes that have shaped the PDD has been challenging and restricted by the limited mechanistic understanding of ecological and evolutionary processes from correlative or comparative methods (30). Instead, by combining paleoenvironmental reconstructions with spatially explicit models of ecoevolutionary processes, simulation models offer a unique but largely underused resource (but see, for example, refs. 3134) to directly explore the evolutionary mechanisms behind the origins of biodiversity patterns in silico (30, 34). In this study, we explored the origins of the PDD in three steps. First, we quantified the ubiquity of the PDD across a wide range of plant and animal taxa. We then tested whether contemporary climate conditions can explain variation in species diversity among continents using a correlative approach. Finally and most innovatively, we assessed the role of paleoenvironmental dynamics in driving pantropical biodiversity patterns using a spatially explicit simulation model of diversification coupled with a paleoenvironmental reconstruction of temperature, aridity, and plate tectonics over the past 110 Ma. Specifically, we explored how major changes in the paleoclimate and plate tectonics have shaped speciation and extinction rates throughout the Mesozoic and Cenozoic and the spatial distribution of phylogenetic diversity. We asked the following questions. 1) Are present-day climatic differences between continents sufficient to explain differences in species diversity? 2) Could deep-time environmental dynamics have driven the emergence of present-day diversity differences between regions? 3) How has spatial and temporal variation in speciation and extinction rates shaped spatial diversity patterns, and how have mountain building, island formation, global cooling, and aridification influenced these rates? 4) What is the deep-time signature of diversification and dispersal in spatial patterns of phylogenetic diversity?

We assessed the ubiquity of the PDD pattern across a broad range of taxa using distribution data for over 128,000 species of plants from 165 families (35) and over 32,000 species of terrestrial vertebrates from 71 bird, mammal, and amphibian orders and 7 squamate reptile infraorders (3638). We found that 38 vertebrate and 63 plant clades, encompassing 95% of all terrestrial vertebrate species and 92% of all plant species assessed, are distributed across tropical moist forests in all three of the investigated regions: Neotropical, Afrotropical, and Indomalayan (3). For these pantropical taxa, we found a systematic pattern of lower -diversity in the Afrotropics, with 23 vertebrate clades and 34 plant cladesrepresenting 81 and 72% of all vertebrate and plant species, respectivelyshowing a PDD pattern (Fig. 1 A and B and Dataset S1). This result highlights that a disproportionate number of species belong to large tropical radiations, including anuran amphibians, passerine birds, gekkotan squamates, chiropteran mammals, and orchids, and these ecologically distinct but extraordinarily diverse clades show strikingly similar uneven diversity across the tropics.

Evenness of diversity in tropical moist forests across biogeographic regions in pantropically distributed taxa. Ternary plots show the proportions of diversity per clade found in Neotropical, Afrotropical, and Indomalayan tropical moist forests (green, orange, and purple triangles, respectively) for (A, Left) plant families; (B, Left) mammal, bird, and amphibian orders and squamate infraorders; and (C, Left) mechanistic model simulations. Species richness maps highlight examples that show the PDD: (A, Right) Arecaceae (palms; richness measured across botanical countries), (B, Right) Trogoniformes (trogons and allies), and (C, Right) one simulation.

To explore whether variation in contemporary climate might explain the PDD, we compared the distribution of mean annual temperature (MAT), mean annual precipitation (MAP), and annual potential evapotranspiration (PET) in the present day across each of the three tropical moist forest regions. Our results support the assertion that the Afrotropics contain only a subset of the total environmental variation present in the Neotropical and Indomalayan regions (12), corresponding to an absence of regions with very high MAP (>3,300 mm) and very low MAT (<13C) (Fig. 2A and SI Appendix, Figs. S1 and S2). It has been suggested that high-precipitation environments in the Neotropics and Indomalaya, with no analog in the Afrotropics, are among the worlds most species rich (12). The effects of temperature and precipitation on species diversity have been suspected to be the indirect result of their positive influence on primary productivity (23). However, we found that both median and maximum PET, a measure of productivity, were actually highest in the Afrotropics, where diversity was lowest (SI Appendix, Fig. S1).

Present-day environmental variation among tropical moist forest regions and species richness relationships. (A) Ternary color-coded map of tropical moist forest regions based on PET (955.4, 1,953.6 mm/y), MAP (389.8, 6,527.3 mm/y), and MAT (5.3, 28.5 C). (B) Regression coefficients from GLS models of log(species richness + 1) as a function of PET, MAP, and MAT for four vertebrate clades (squamate reptiles, mammals, birds, and amphibians) and three regions (Neotropics, Afrotropics, and Indomalaya), with each clade and region tested separately. *Statistical significance after Holms correction for multiple comparisons.

We quantified the relationships between -diversity, MAT, MAP, and PET in 110- 110-km grid cells across tropical moist forest regions in four vertebrate clades for which high-resolution spatial data were available (amphibians, squamate reptiles, mammals, and birds) using generalized least squares (GLS) models accounting for spatial autocorrelation (Fig. 2B), and we found only weak support for a general relationship between richness and climate. Of the 36 relationships tested, only 4 relationships were significant after correcting for multiple comparisons (P < 0.05; Holms correction) (SI Appendix, Table S2), and these significant relationships had a small effect size (Fig. 2B). For example, a 400-mm gradient of MAP within the Neotropics predicted a difference of 2 squamate species, while that same difference, as found on average between moist forests of the Neotropics and Afrotropics, was associated with an average difference of 18 species between the continents. Our results are also contrary to findings from several studies on plant diversity (12, 39, 40), bringing into question the generality of a present-day climaterichness relationship across taxa and spatial scales within tropical moist forests and the role of contemporary climate as the primary driver of tropical diversity.

To investigate how paleoenvironmental dynamics have shaped present-day patterns of biodiversity across tropical moist forests, we implemented a spatially explicit process-based simulation model of diversification (34) using global paleoenvironmental reconstructions of temperature and aridity dynamics from the Mid-Cretaceous (41). We ran the simulation model 500 times, starting with a single ancestral species distributed throughout the equatorial tropics at 110 Ma. We explored a scenario of pantropical origination corresponding to the ancestors of tropical lineages originating around 120 to 100 Ma (42, 43), before radiating substantially following the CretaceousPaleogene boundary (4446). This period also coincides with the splitting of the American and African continents, opening the Equatorial Atlantic Ocean, and the formation of modern megathermal moist forest ecosystems (16, 47). Our model, implementing only a parsimonious set of ecoevolutionary processes (dispersal, environmental filtering, environmental niche evolution, and speciation) and one additional constraint on dispersal into arid sites, shows that plate tectonics coupled with changes in paleotemperature and aridity can help explain the systematic variation in species diversity across tropical moist forests.

The model reconstructed a range of tropical biodiversity patterns across tropical regions and along latitude. Of the 500 simulations, 106 resulted in total extinction or generated diversity greater than 12,500 species, a threshold beyond which simulations become computationally intractable. The remaining 394 simulations generated a gradient of diversity with latitude, with species richness being negatively correlated with absolute latitude (mean Spearmans = 0.60, range = [0.76, 0.12]). Furthermore, 221 of the complete simulations (56%) generated pantropical diversity, and 169 of these (42%) generated the PDD pattern seen in the empirical data (Fig. 1C and SI Appendix, Fig. S3). To investigate the sensitivity of broad-scale patterns of species distributions to the model parameters, we fitted generalized linear models with a binomial link function of a pantropical index (whether a simulation generated diversity in all three tropical regions) and a pantropical disparity index (whether simulations generated lower diversity in Afrotropical than in Neotropical or Indomalayan regionsthe PDD) and model parameters. We found that when rates of temperature niche evolution were high, temperature niche widths were narrow, and when the speciation threshold was high, simulations were less likely to generate pantropical diversity (SI Appendix, Table S4) or the PDD (SI Appendix, Table S5). Under these parameters, lineages rapidly evolve unsuitable thermal tolerances, driving range collapses from mismatches with the environment. This resulted in extinction events outpacing speciation events, leading to total extinctions in the Afrotropics (67 simulations) and Indomalaya (163 simulations) and preventing the establishment of a pantropical distribution. Instead, simulations with stricter niche conservatism ( < 0.01) regularly generated lineages present in all three tropical regions and a strong PDD (169 of 221 pantropical simulations), as species with low rates of thermal niche evolution maintained adaptation to the megathermal environment through the relatively stable temperature changes of the Cenozoic in the equatorial tropics (48, 49). This result reinforces other recent simulation studies, which also found that niche conservatism is instrumental in generating realistic biodiversity gradients (32, 33).

We found that species richness patterns across simulation outputs were positively correlated with observed richness patterns for vertebrate and plant taxa distributed in all tropical regions (Fig. 1). The highest recorded Spearman correlation coefficients between species richness across 110- 110-km grid cells for each vertebrate clade and completed simulations ranged from 0.49 to 0.91, with a median of 0.78 (n = 22), and correlation coefficients for species richness summarized within botanical countries for plant families ranged from 0.25 to 0.82, with a median of 0.61 (n = 34). Very few clades had correlation coefficients of <0.5, and those that did typically had idiosyncratic diversity patterns that did not match the more general features of the PDD. For example, the Anguimorpha (monitor lizards and allies) showed a PDD with only 3 species found in the moist forests of the Afrotropics, compared with 26 and 91 in Indomalaya and the Neotropics, respectively. However, Neotropical hot spots of diversity for the Anguimorpha are located in Central America with the clade being almost entirely absent from the Amazon basin, contrary to the simulation model predictions (Fig. 1C). This suggests that the simulation model can capture general features of pantropical diversity, while the biogeography of individual taxa requires further examination.

Previous correlative models incorporating historical variation in area and productivity have also provided a close fit to global patterns of species richness (14, 18, 50), yet these models have not been explicitly evolutionary and have been unable to explicitly investigate macroevolutionary processes shaping biodiversity patterns. On the other hand, similar mechanistic models have been used to explore the emergence of terrestrial diversity gradients (32, 33), although the origin of the PDD has not been investigated in previous studies. For example, Rangel et al. (33) looked exclusively at the evolution of Neotropical diversity, while the global study of Saupe et al. (32), which considered paleoenvironmental change over the past 120 ky, successfully reconstructed the latitudinal diversity gradient but overpredicted diversity in Afrotropical moist forests; therefore, it did not capture the PDD. The inclusion of extended paleoenvironmental reconstructions from the Mesozoic (110 Ma) to the present day (41, 49, 51) in the present study may explain why the model was able to additionally predict pantropical diversity patterns.

To investigate the macroevolutionary dynamics that lead to the diversity differences between the tropical moist forest regions, we extracted spatial and temporal variation in speciation and extinction rates across the subset of simulations that generated the PDD (169 simulations) (Fig. 3). We performed a pairwise comparison of the distribution of mean speciation and extinction rates between regions using Wilcoxon signed-rank tests and found that Indomalaya, but not the Neotropics, had significantly higher rates of speciation compared with the Afrotropics (Neotropics mean = 0.089 0.002 speciation events per lineage per My, Indomalaya = 0.117 0.001, Afrotropics = 0.0830.002), although both the Neotropics and Indomalaya had significantly lower rates of extinction than the Afrotropics (Neotropics = 0.029 0.001 extinction events per lineage per My, Indomalaya = 0.033 0.001, Afrotropics = 0.042 0.002). Our findings unify two alternative hypotheses (2): that both lower speciation rates in the Afrotropics (21, 52) and higher extinction rates in the Afrotropics (15, 25) compared with the other moist forest regions have played a role in shaping the PDD. Moreover, both speciation and extinction rates were significantly higher in Indomalaya than in the Neotropics, resulting in overall higher species turnover, and as such, tropical moist forests in the Neotropics and Indomalaya reached high diversity through alternative pathways.

Macroevolutionary rates and spatial diversity patterns through time from simulation models. (A) Speciation and extinction rates estimated across 1-My intervals within each tropical moist forest region, averaged across models that generated the PDD. Rates were highly stochastic in the Mid-Cretaceous (burn-in period) because species diversity was low, so we present rates from the Late Cretaceous (80 Ma) onward. Several key climatic periods are highlighted with dashed gray lines. The greenhouse climates of the Paleocene and Eocene are highlighted by the PaleoceneEocene thermal optimum (PETM; 56 Ma) and the Early Eocene climatic optimum (EECO; 50 Ma), while global cooling and the transition to an icehouse climate are highlighted by the EoceneOligocene transition (EOT; 34 Ma), the Mid-Miocene climate transition (MMCT; 14 Ma), and the last glacial maximum (LGM; 30 to 10 ka). (B) Species richness patterns standardized and averaged across simulations generating the PDD during six time periods corresponding to the Mid-Cretaceous (100 Ma), Late Cretaceous (69 Ma), Eocene (46 Ma), Oligocene (27 Ma), Miocene (13 Ma), and Pleistocene (340 ka).

The simulation results support the long-term role of aridification in shaping contemporary Afrotropical biodiversity by increasing extinction through range contractions and decreasing the area of opportunity for speciation (16). Presently, Afrotropical moist forests occupy the smallest geographic area of the three regions (2) and are tightly bound by the Sahara, Namib, and Ogaden deserts, but the Afrotropics are considered to have had the largest area of moist forests of any continent during the greenhouse climates of the Paleocene and Eocene (14, 20, 47) (SI Appendix, Fig. S4). A subsequent decrease in area may have begun as early as the Mid-Eocene (25, 53), and it became more pronounced due to rapid global cooling at the EoceneOligocene transition and later during the Middle Miocene climate transition and Late Miocene cooling events (16, 47, 54). Along with simultaneous tectonic rifting activities, these changes altered the distribution of precipitation across the African continent (47, 55, 56). A number of phylogenetic studies have suggested deep divergences between moist forest lineages in eastern and western African dating as early as the Eocene and Oligocene (57, 58), driven by the ancient vicariance of these regions following the expansion of dry habitats (59). According to the simulations, the reduction in the extent of moist forests over time has had legacy effects on the biodiversity of taxa associated with tropical moist forests (2). Specifically, extinction rates were highest in the Afrotropics during the Paleocene and Eocene (Neotropics Paleocene = 0.019 0.0009, Eocene = 0.023 0.0005; Indomalaya Paleocene = 0.018 0.001, Eocene = 0.021 0.0007; Afrotropics Paleocene = 0.032 0.0018; Eocene = 0.028 0.0009), while differences compared with other regions were less marked during the Miocene (Neotropics Miocene = 0.019 0.0009, Indomalaya Miocene = 0.046 0.0005, Afrotropics Miocene = 0.046 0.0009) (Fig. 3 and SI Appendix, Fig. S5).

To assess the causal role of key Earth history changes on emergent biodiversity patterns, we ran simulations that modified the paleoenvironmental reconstructions by removing the aridity constraint in the Afrotropical realm from the Early Cretaceous and from the Early Miocene. These supporting simulations showed that lifting aridity constraints in the Afrotropics from the Miocene onward did not significantly influence diversity (paired Wilcoxon signed-rank test P = 0.07), while simulations with the aridity constraint removed from the Early Cretaceous showed significantly higher diversity than unmodified simulations (original simulations generated on average 44.8% of the diversity of modified simulations; Wilcoxon test P = 0.027), reversing the PDD in 66% of simulations (SI Appendix, Fig. S6). In particular, when the constraint of aridity was removed from the Cretaceous, diversification rates were higher, driven by the opening up of a large area for lineages to radiate, including many of the southern and northern parts of the continent (16, 49). Our results, based on reconstructions of paleoaridity dynamics, suggest that aridification played an early and sustained role in suppressing Afrotropical moist forest diversity over a long period of the Cretaceous and Cenozoic.

A strong association between plate tectonics and the formation of uneven tropical diversity across regions emerged from the simulations, with the rise of the Andes playing a key role in the Neotropics. Dynamic tectonic activity has been suggested to be the cause of exceptional biodiversity in both the Neotropics and Indomalaya (15, 19) as both these regions have active continental margins compared with the Afrotropics, which lies at the center of the African plate and whose major topographic features are the result of rifting (47, 56). The formation of the Andes, resulting from plate convergence between the South American continent and the subducting oceanic Nazca plate, has been proposed to foster lineage diversification, acting as a source of diversity across the Neotropics (19, 60). Accordingly, our simulations showed increasing rates of diversification from the Paleocene to the Oligocene in the Neotropics (Fig. 3 and SI Appendix, Fig. S6) associated with the early rise of the Andes in the paleoreconstruction and the associated increase in environmental heterogeneity (SI Appendix, Fig. S7). To further demonstrate the role of the Andes in forming Neotropical diversity, following ref. 33, we ran simulations in which Andean orogenesis was removed, holding a constant low elevation from 110 Ma onward. We found that removing orogeny led to significantly lower Neotropical diversity (modified simulations generated on average 1.6% of the diversity of the original simulations; paired Wilcoxon signed-rank text P < 0.001), reversing the PDD in more than 90% of the modified simulations (SI Appendix, Fig. S6).

The Indomalayan realm, in addition to the Neotropics, is both one of the Earths most biodiverse and tectonically active regions. The collision of the Indian and Eurasian plates led to the formation of some of the worlds largest mountain chains, promoting speciation in South and Southeast Asia, and may be the ultimate driver of several biodiversity hot spots (6163). The collision of the Australian and Eurasian plates in the Early to Mid-Miocene led to the formation of the topographically complex Southeast Asian archipelago andcombined with dynamic sea-level changesmay have led to the origin of locally endemic biotas on intermittently isolated islands (64, 65). In the simulations, increasing rates of diversification in Indomalaya from the onset of the IndianEurasian plate collision in the Late Eocene until the Late Oligocene (25 Ma) suggest a key role of habitat complexity in shaping the diversification of this region (Fig. 3). Furthermore, high rates of speciation during the collision of the Australian and Eurasian plates in the Mid-Miocene also point to the role of either increased topographic complexity or island formation as key factors shaping the biodiversity (66). To investigate the origins of Indomalayan biodiversity and tease apart the effects of island isolation and mountain building, we ran simulations with modified landscapes, removing the cost of dispersal over water, as well as environmental heterogeneity following orogenesis. While reducing island isolation did not change diversity (Wilcoxon test P = 0.92), reducing heterogeneity caused significantly lower diversity (modified simulations generated on average 12.9% of the diversity seen in the original simulations; Wilcoxon test P = 0.002), reversing the PDD in >80% of the modified simulations (SI Appendix, Fig. S6). The role of isolation, while not integral to the establishment of high Indomalayan biodiversity in the simulations, has been shown to be important in clades with low dispersal capacities (67). We did not model variation in dispersal traits in this study; however, this may help to explain residual variation in biodiversity across lineages.

Taken together, variation in rates of diversification in the simulation models and the landscape modification experiments suggests a predominant role of active mountain building in the formation of the PDD. The Afrotropics are as topographically heterogeneous as the Indomalayan and Neotropical regions, with several major topographical features intersecting the tropical moist forest biomeincluding the Central African Rise, Cameroon Highlands, and Eastern Arc (2, 47, 68), some of which are centers of species richness (69). However, in the Afrotropics, mountain topography was generally more stable over time and associated with more arid continental regions (2). Hence, our results show that the dynamic temperature heterogeneity provided by active mountain building in mesic regions creates a mosaic of opportunities for species to adapt to different conditions, leading to high rates of diversification that act not only as cradles of diversification but also, as museums, refugia, and innovation hubs (70).

Speciation and extinction rates through time in tropical moist forests show complex patterns associated with both region-specific dynamics and global temporal trends in paleoenvironmental conditions. In the simulation model, speciation was dictated by the establishment of geographic isolation driven by temperature, aridity, or oceanic barriers, and as a result, idiosyncratic speciation dynamics (Fig. 3) were more strongly determined by local geoclimatic histories. On the other hand, extinction in the model was based on mismatches between species temperature niches and the landscape, and therefore, climate change was the primary driver of extinction, which might explain congruent trends in extinction dynamics resulting from global climate change over the past 110 Ma. Our simulations showed that the Late Paleogene period was characterized by increasing extinction rates, punctuated by a burst in extinction rates associated with 10 My of cooling climate at the EoceneOligocene transition (the big chill) (SI Appendix, Fig. S4), with extinction rates reaching a peak across all three regions in the Mid-Oligocene (Fig. 3 and SI Appendix, Fig. S5) (Oligocene average extinction rate in Afrotropics = 0.051 0.001, Indomalaya = 0.052 0.001, Neotropics = 0.055 0.001). Global cooling across the EoceneOligocene transition corresponds empirically to one of the Paleogenes climate-driven global extinction events (71), which saw high rates of turnover in many taxa, including marine mollusks, tropical broadleaf plants, and terrestrial mammals (7274). Further, fossil evidence has highlighted large decreases in diversity in Neotropical and Afrotropical forest biomes at this time (16).

A second shared extinction peak of a greater magnitude was recorded during the Late Neogene and Quaternary periods (Fig. 3 and SI Appendix, Fig. S5) (Pleistocene Afrotropical extinction rate = 0.119 0.004, Indomalaya = 0.102 0.003, Neotropics = 0.072 0.003), resulting from global cooling and temperature oscillations associated with glaciation events. During these periods in the simulations, sharp changes in temperature (SI Appendix, Fig. S4) led to extinctions biased toward taxa at the upper and lower tails of the thermal niche distribution on each continent (SI Appendix, Fig. S8). This pattern was more severe in the Afrotropics and Indomalaya, as these regions had fewer species with thermal niches in the cold tails of the distribution and more species in the warm tails of the distribution (SI Appendix, Fig. S8). A possible explanation for this finding is that, while the Afrotropics are colder on average than the Neotropics or Indomalaya, the region had lower temperature heterogeneity overall and therefore, far fewer opportunities for species to adapt to the more extreme temperatures that increased in area during the Quaternary. Further, the large number of species in the warm tails of the thermal niche distribution in both Indomalaya and the Afrotropics were driven extinct by rapidly cooling climates (SI Appendix, Figs. S4, S8, and S9).

Temperature changes, such as those associated with the EoceneOligocene transition and Quaternary glaciations, drive range contractions due to a mismatch between thermal tolerances and available habitat, and in some cases, they drive total extinction of the species. Such temperature changes have been hypothesized to be a major driver of extinctions in tropical moist forests (11). However, in other cases where refugia exist, species are buffered from extinction (75), and temperature changes facilitate fragmentation of populations or sustain the persistence of already fragmented populations, leading to speciation (76). Our results show that both periods of high extinction coincided with high rates of speciation across all continents (Oligocene Afrotropical speciation rate = 0.106 0.003, Indomalayan = 0.128 0.002, Neotropical = 0.106 0.002; Pleistocene Afrotropical speciation rate = 0.141 0.004, Indomalayan = 0.138 0.002, Neotropical = 0.168 0.004) (Fig. 3 and SI Appendix, Fig. S5). These results together highlight the processes behind the dual role of climate change in diversification, where heterogeneous landscapes such as mountains act as both species pumps and refugia, as has been suggested for many Andean lineages (7, 19, 22, 28, 7779). The role of glacial oscillations in generating species-level diversity, compared with intraspecific patterns of genetic divergence, is still debated, with population-level studies and phylogenetic studies showing evidence for both (e.g., refs. 80 and 81). In our simulations, the duration of speciation was parameterized to be longer than the timescales considered during the Pleistocene period, and so, the formation of new species in that era was due to the sustained isolation of lineages that began diverging before the Pleistocene.

The phylogenetic structure of regional assemblages contains the signature of both the dispersal history and diversification dynamics that have shaped biodiversity patterns across regions (20, 82, 83). Using the net relatedness index [NRI (84)], we measured the degree to which species within tropical moist forests in different regions were more closely related (phylogenetic clustering) or more distantly related (phylogenetic overdispersion) than expected based on random sampling of species. In vertebrate clades showing the PDD pattern, we found support for significant phylogenetic clustering in 56% of clades in the Afrotropics, 61% in Indomalaya, and 74% in the Neotropics, compared with only 4% of clades in the Neotropics and Indomalaya that showed significant overdispersion and 8% of clades in the Afrotropics. The Afrotropics and Indomalaya had 34% of clades that showed distributions not significantly different from random, compared with 21% in the Neotropics, and the Neotropics on average were more phylogenetically clustered (SI Appendix, Fig. S10). This supports the assertion that tropical moist forests are generally composed of in situ endemic radiations (Fig. 4 A and B), which is consistent with an out-of-the-tropics model of diversification (82, 83, 85) rather than dispersal from other biomes, and also highlights the role of isolation of the Neotropics in establishing a highly clustered biota (20). However, contrary to findings from a study on palms (20), we observed that palms in the Afrotropics were not more likely to be randomly distributed than those in Indomalaya, and we found that, at the level of botanical country, palms were phylogenetically clustered in the Afrotropics (Fig. 4). This result supports the finding that phylogenetic clustering is increasingly common at larger spatial scales, due to the capturing of in situ diversification dynamics (86).

NRI measured across (A) palms (family Arecaceae; 9.6, 0.8) in botanical provinces, (B) anuran amphibians (16.8, 0.1) in biomes, and (C) a gen3sis simulation (40.4, 0.5) matching Figs. 1C and 3B, alongside tropical moist forest (TMF) biomes mapped onto associated phylogenies. Gray, non-TMF; green, Neotropics ; purple, Indomalaya; yellow, Afrotropics.

As a final evaluation of the validity of the simulation model, we estimated the ability of the model to reproduce NRI patterns in simulations showing a PDD. In our simulations, we found that all three tropical moist forest regions were significantly phylogenetically clustered in more than 95% of cases. More frequently, we found that tropical moist forests in Indomalaya and the Neotropics were more phylogenetically clustered than in the Afrotropics, similar to the empirical trend, and Spearman correlations between simulated and empirical NRIs were generally high (Spearmans = 0.22 to 0.89, median = 0.72) (Fig. 4). However, contrary to the empirical data, we found that Indomalayan assemblages were generally more clustered than those in the Neotropics (SI Appendix, Fig. S9). We attribute this pattern in the simulated data to the connection of the Afrotropics and Neotropics during the initial conditions of the simulation and to the isolation of the Indomalayan moist forests during much of the Cenozoic due to harsh aridity barriers to the north of the region, preventing dispersal into other biogeographic regions. However, empirically determined dispersal tracks between Indomalaya and the Palearctic, Afrotropics, and Australasia are widely recognized (15, 25), and many taxa originated after the split of the American and African continents. Investigating the role of long-distance dispersal in establishing patterns of phylogenetic diversity in a process-based simulation framework would be useful for understanding the relative contribution of in situ vs. dispersal-based processes in driving the PDD and other tropical biodiversity patterns.

This study shows how paleoenvironmental change over the Mesozoic and Cenozoic has shaped variation in species diversity across tropical moist forests. Taken together, our results highlight the difficulty in assigning a proximal cause to any single process in shaping the PDD and instead, highlight the complex roles of habitat heterogeneity, aridity constraints, and temperature changes, as well as the importance of specific events in Earths history, in shaping global biodiversity patterns. We demonstrate that the origin of the PDD predates the EoceneOligocene transition (Fig. 3), supporting a deep history of the pattern (27, 87). However, the stark contrasts between tropical regions consistent with the PDD pattern we observe today were reinforced and consolidated during the Miocene, when extinctions rates were low in the Neotropics and speciation rates were high in Indomalaya relative to the Afrotropics. These contrasts further solidified during the Pleistocene, supporting an additional, but not ultimate, role of glacial oscillations. The model used in this study (34) can be applied to test hypotheses about spatial diversification dynamics and makes it possible to directly manipulate key Earth history events to better understand how biodiversity patterns emerge, a feature hard to achieve with currently available correlative or phylogenetic comparative methods.

Using only a simple set of ecoevolutionary rules played out across a dynamic landscape, we have demonstrated that we are able to reproduce emerging biodiversity patterns under a set of parameter combinations, particularly when thermal niches are phylogenetically conserved. The ability to reconstruct uneven tropical diversity highlights how simulation-based analyses can be used to explore different hypotheses of the processes shaping biodiversity gradients around the globe. In this study, we explored a single model of diversification and niche evolution, excluding a range of complex ecological processes, such as direct interspecific competition, which may explain residual variation between the simulated and empirical diversity patterns. We also applied a subset of parsimonious and generalized initialization and dispersal scenarios to taxa with a diverse range of biogeographic and evolutionary histories. We consider an important next step to be investigations of how adding or subtracting different ecological and evolutionary model components changes biodiversity patterns (34). In addition, the parameters of simulation models could be tailored to specific clades based on biogeographic reconstructions from molecular and fossil data to understand how processes such as long-distance dispersal have shaped present-day phylogenetic diversity.

We obtained matching data on the geographic distribution and phylogenetic position of extant species of terrestrial vertebrates collected through the VertLife project (https://vertlife.org/) in association with Map of Life (https://mol.org/). Phylogenies were downloaded from VertLife and follow refs. 36 and 8890. Distribution data for birds came from ref. 36, and for squamates, they came from the Global Assessment of Reptile Distributions (37). For mammals and amphibians, we modified distributions from the International Union for Conservation of Nature (IUCN) (38) to match the names of the respective phylogenies, and for squamate reptiles, we matched names following ref. 91. For plants, we used regional checklists of all 189 families presented in the Kew worldwide database (35). We used checklists corresponding to the most detailed level3 polygons of botanical countries from the Taxonomic Databases Working Group (https://www.tdwg.org/). We investigated empirical patterns of diversity in 189 plant families and 78 vertebrate clades (bird, mammal, and amphibian orders and squamate reptile infraorders). We identified the subsets of these clades that were pantropically distributed, here defined as having at least one-third of the species found in the tropical moist forest biome (3) and occurring in all three of the considered biogeographic regions (Neotropical, Afrotropical, and Indomalayan) for vertebrates and botanical countries that overlap these biomes for plants. We did not consider species found in Madagascar in the Afrotropics. We quantified the evenness of the distribution of species diversity between the regions for the pantropically distributed empirical data (Fig. 1 A and B and Dataset S1). Distribution data for plants were less complete than the corresponding data for vertebrates, and so, we focused our quantitative analysis on vertebrate clades.

To characterize the relationships between present-day species richness and climate in each tropical region, we estimated vertebrate species richness in 110- 110-km equal-area grid cells for birds, mammals, amphibians, and squamate reptiles separately across sites within the tropical moist forests on each continent. We also collated data on three major axes of environmental variation across tropical sites: MAT, MAP, and annual PET. MAT and MAP data were obtained from Chelsa at 30arc s resolution (92), and PET data were obtained from Environmental Rasters for Ecological Modeling (ENVIREM) at 2.5arc min resolution (93). All three variables were resampled at 110- 110-km resolution using a Behrmann equal area projection to match the species distribution data (Dataset S2). We fitted GLS models of log (+1)-transformed species richness values, with MAT, MAP, and PET standardized to unit variance for the comparison of regression coefficients across variables measured in different units. To account for spatial autocorrelation in the model, we included a Gaussian correlation structure in the error terms variance/covariance matrix. We fitted separate models for each vertebrate class and each continent, totaling 36 models.

Paleoenvironment was reconstructed for the entire globe for the last 110 My at a temporal resolution of 170 ky and a spatial resolution of 2 and was characterized by approximate air surface temperature (related to MAT) and an aridity index (related to MAP and PET), following ref. 41 (Dataset S3). Air surface temperature was reconstructed by combining 1) paleotopography, estimated from paleoelevation models (94), with 2) reconstructions of paleo-Kppen climatic zones based on the geographic distribution of lithologic indicators of climate (95, 96), modified using the current temperature-lapse rate for each Kppen zone based on the current elevation and MAT downloaded from WorldClim2 (97). The aridity index was reconstructed from the paleo-Kppen bands and given a value of one for the arid Kppen regions and zero for all the other bands. We additionally modified the input in five ways for use in the landscape modification experiment. We reduced the temperature heterogeneity associated with orogenesis of the Andes region from 110 Ma, we held temperatures of the Indomalayan region at a constant value, we removed the cost associated with crossing water in the Southeast Asian archipelago, and we changed arid cells in the Afrotropics to nonarid cells from 110 and 23 Ma (further details on the reconstruction are in SI Appendix, Fig. S11).

We implemented the spatial model of diversification using the general engine for ecoevolutionary simulations, gen3sis (34). Each simulation followed the diversification of a clade from a single ancestral species distributed broadly throughout nonarid sites within 25 of the equator 110 Ma (Movie S1). We also tested the sensitivity of the pantropical diversity patterns to different initial ancestral ranges, including an exclusively extratropical ancestor, and found that the Afrotropics had lower diversity under these alternative starting conditions (further details are in SI Appendix, Fig. S12). Each simulation follows a clades radiation from the initial species throughout 110 My of reconstructed paleoenvironmental changes across 2 grid sites on the global landscape, considering four major processes: dispersal, environmental filtering, niche evolution, and speciation.

At each time step (170 ky, 660 time steps in total), each population could disperse into surrounding grid sites from a dispersal kernel drawn from a Weibull distribution centered on 2 (222 km of latitude at the equator) with shape .

The presence of species i in site s was determined by a match between the species temperature niche width (i) and the local temperature value Ts. Each species could be present in a site if |Ti|>Ts, where Ti is the temperature niche center. One of the major constraints for the distribution of tropical moist forest taxa is water availability (40). In this study, the paleoaridity data are derived from a binary layer, thus limiting modeling in an aridity niche in a way comparable with that of the temperature niche. Therefore, to implement environmental filtering based on water availability, we place a hard constraint on species entering arid grid cells. This constraint prevents species from entering arid grid cells, and the assumption is supported by empirical evidence that biome shifts between forest and arid biomes are exceptionally rare (98). Extinction occurred when a species no longer occupied any grid cells as a result of mismatches between the species environmental niche and the environment.

Evolution of the temperature niche trait Ti followed a Brownian motion model of trait evolution, where the value of Ti at increasing time intervals of t is equal to the value of Ti at time t, plus a value drawn from a normal distribution with a mean of zero and SD of .

Speciation followed the biological species concept (99) in which species are considered reproductively isolated populations. Populations of a species that became geographically isolated from each other diverged genetically at each time step, and after divergence had crossed a speciation threshold (S), the populations became new distinct species. This equates to a BatesonDobzhanskyMuller model of genetic incompatibility (99).

We ran 500 simulations over a variable range of the four main model parameters, determined where possible based on empirical data and subsequently based on a preliminary exploration of the parameter space (SI Appendix): = [0.04, 0.1], corresponding to a niche width of 2.6 C to 7C; = [2, 15], corresponding to a dispersal kernel with a right skew to include more long-distance dispersal values for low values of or a dispersal kernel with values centered more closely at 2 for higher values of ; = [0.001, 0.02], corresponding to a range of the temperature variance of the Brownian function from 1.6 C to 1.3C for each 170-ky time step, which is within the range found by ref. 100; and S = [1.5, 3], corresponding to a time interval of 2.5 to 6 My, which is based on estimated times for reproductive isolation to establishment (101). This range is towards the upper limit of the empirically estimated timing for speciation (102), however this was due to the constraints of computational feasibilitywhen the parameter value was low, reflecting very short speciation times, the number of species increases drastically, preventing the completion of the simulations (SI Appendix, Fig. S13). Due to the computational cost of running simulations, we sampled model parameters using Sobol sequences (Dataset S4), a quasirandom number generator that samples parameters evenly across the parameter space. Further details on the simulation model framework, model parameters, initial conditions, paleoenvironmental reconstructions, and landscape modification experiment are in SI Appendix.

In the complete simulations, we estimated species diversity within the tropical moist forests boundaries in the same way as for empirical data (Dataset S4). We fitted generalized linear models of the pantropical index (a binary variable representing whether simulations generated species in all three regions or not), the pantropical disparity index (a binary variable representing whether simulations generated the lowest diversity in the Afrotropics), and simulation parameters. We also aggregated simulated species richness to a 110- 110-km resolution and a botanical country resolution to match the empirical vertebrate and plant distribution data, respectively. Then, as a measure of goodness of fit of the simulations, we estimated pairwise Spearman correlation coefficients of species richness across grid cells and botanical countries for each simulation with each pantropically distributed vertebrate and plant clade, respectively.

To investigate causation of uneven pantropical biodiversity in the simulation model, we manipulated paleoenvironmental reconstructions, subtracting key Earth history events to compare with unmodified simulations, following ref. 33. We performed key experimental manipulations focused on each tropical moist forest region addressing key hypotheses for the generation or suppression of biodiversity. In the Afrotropics, we removed the aridity constraint from either the Early Cretaceous or the Early Miocene. In the Neotropics, we removed the formation of the Andes. In Indomalaya, we reduced the dispersal distances between islands in the Southeast Asian archipelago and also removed the environmental heterogeneity associated with orogeny. We ran the simulation model across these five modified inputs using the parameters from the 10 best-fitting models (models that had the largest number of strong positive correlations with empirical clades showing a PDD pattern; Spearmans > 0.7). We ran each model three times to account for stochasticity. Further details on the experimental procedure and results can be found in SI Appendix.

To identify trends in the spatial and temporal patterns of diversification, we estimated speciation and extinction rates in 1-My time slices for each of the 169 simulations that generated the PDD. Speciation and extinction rates were highly variable during the first 30 My of the simulation, owing to the stochasticity associated with the small number of species. Therefore, we considered the period from 110 to 80 Ma as a burn-in period, and we compared the distribution of these macroevolutionary rates from 80 My to present day between the Neotropics, Afrotropics, and Indomalaya. We used pairwise Wilcoxon signed-rank tests to test for a difference in the mean extinction and speciation rates across regions. We also investigated speciation and extinction rates separately for each geological era (Late Cretaceous, Paleocene, Eocene, Oligocene, Miocene, Pliocene, and Pleistocene) (SI Appendix, Fig. S6). To investigate how the evolution of the temperature nichetrait drove patterns of speciation and extinction across lineages, we looked at the evolution of this trait through time. We took the mean Ti across all populations of each lineage at each time step and investigated how the distribution of the temperatureniche trait varied through different geological eras in a single simulation, matching Fig. 1C (SI Appendix, Figs. S8 and S9, and Movie S2).

To look at how different environmental features differed between tropical moist forest through time, we estimated which grid cells from the paleoenvironmental reconstruction corresponded approximately to this biome across different biogeographic regions through time by defining these cells as those with MAT > 18C and aridity index = 0. This equates to a rough approximation of a megathermal tropical environment likely to be dominated by tropical moist forests (15) (Movie S3). We then recorded changes in mean temperature (degrees Celsius), temperature variance (SD; degrees Celsius), mesic area (kilometers2), and habitat fragmentation (SI Appendix, Figs. S4 and S7). Habitat fragmentation was estimated as the proportion of disconnected sites relative to area over time (SI Appendix, Fig. S4). A fragmentation value of 100 would mean that each cell in a tropical region is a unique cluster, while values close to zero mean that all cells in the region are connected as a single cluster during the period.

To understand the relative role of dispersal compared with in situ diversification dynamics in structuring the phylogenetic relatedness of species within tropical moist forests, we calculated the NRI, a measure of the phylogenetic distance between co-occurring species in an assemblage standardized by the expected phylogenetic distance under a null model of community assembly (84). We used the independent swap null model, which maintains richness of sites and frequencies of species in the dataset, using the mpd.ses function in the picante package in R (103). We estimated NRI across biomes in different regions, as biomes represent evolutionary arenas of diversification suitable for comparison (3). We calculated the NRI for all 23 vertebrate clades showing a PDD pattern using a randomly sampled phylogeny from the posterior distribution of the respective taxon (Dataset S5). We also calculated the NRI for palms across botanical countries, possible due to the well-sampled phylogeny available for this clade, which includes placing species based on morphological and taxonomic data where molecular data were unavailable (104). As done with the comparison of species richness, we calculated pairwise Spearman correlation coefficients of NRI between empirical and simulated datasets.

Data and R scripts used in this study are deposited in a public repository on EnviDat, https://www.envidat.ch/dataset/data-from-hagen-skeels-etal-pnas. All other data are included in the manuscript and/or supporting information. Previously published data were also used for this work: vertebrate phylogenetic data (36, 8890), vertebrate distribution data (37, 38), plant distribution data (35), and palm phylogenetic data (105).

We thank Samuel Bickels, Melissa Dawes, and the Macroevolution and Macroecology Group at the Australian National University for helpful feedback. We thank the curators and contributors to the Kew Plants of the World online database, the IUCN distribution database, and other vertebrate spatial distribution and phylogenetic databases used in this study. We also thank Charles Novaes de Santana, Benjamin Flck, and Fabian Fopp for technical support. R.E.O. acknowledges the support of the German Centre for Integrative Biodiversity Research (iDiv) Halle - Jena - Leipzig, funded by the German Research Foundation DFGFZT 118 Grant 202548816. L.P. was supported by the Swiss National Science Foundation Project Bigest 310030-188550.

Author contributions: O.H., A.S., and L.P. designed research; O.H., A.S., and W.J. contributed new reagents/analytic tools; O.H., A.S., and R.E.O. analyzed data; and O.H., A.S., R.E.O., W.J., and L.P. wrote the paper.

The authors declare no competing interest.

This article is a PNAS Direct Submission.

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Earth history events shaped the evolution of uneven biodiversity across tropical moist forests - pnas.org

By Michael Le Page

A concept illustration of blood cells and Plasmodium parasites

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Cheap rapid tests for malaria have helped drive down the prevalence of the disease in many parts of Africa. But just 15 years or so after their introduction, stealthy malaria parasites have evolved that can no longer be detected by the standard rapid tests.

This is a major threat to malaria control, says Jane Cunningham at the World Health Organization Global Malaria Programme in Geneva.

In many African countries, only people whose rapid test results are positive get treated. But in Eritrea around 2016, health workers noticed that many children who appeared to be really sick with malaria were testing negative. When medics looked at blood samples under a microscope, they could see many of the children were indeed infected.

It was a crisis situation, says Cunningham. They thought there was something wrong with the test.

Instead, her team found that up to 80 per cent of the malaria parasites in the area have mutations that mean they no longer produce the two proteins called pfhrp2 and pfhrp3 detected by the rapid tests.

Continued use of these rapid tests is selecting for [parasites without the two marker proteins] to proliferate, says Cunningham.

Her team then did a survey in neighbouring Ethiopia. We didnt find as high a prevalence as in Eritrea, but we found really concerning levels, she says.

Evolution is often a trade-off, with mutations that provide an advantage in one way being a disadvantage in another. But the parasites seem to thrive without the pfhrp proteins, whose function isnt known.

Areas with the mutant malaria parasite are switching to tests that detect another protein, but these tests arent yet as reliable they are less heat stable, for instance. Switching to microscope detection isnt an option in most places as it requires expensive equipment and skilled technicians.

Ideally, says Cunningham, rapid tests would look for several biomolecular targets in the parasites at once, and ones that play a key role in the biology of the organisms, so it is hard for them to mutate. But this makes tests more complex and expensive.

It is common for viruses, bacteria, parasites and cancers to evolve resistance to treatments, but evolving to evade a test is much more unusual this might be the first clear example. Some hepatitis B viruses have mutations that mean they are missed by tests, Cunningham says, but it isnt clear if this is due to selection as a consequence of testing.

Some countries are now using rapid tests to detect the coronavirus,SARS-CoV-2, which in theory could evolve to evade them.

Journal reference: Nature Microbiology, DOI: 10.1038/s41564-021-00962-4

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Parasite evolution is making it harder to detect and treat malaria - New Scientist News