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Seeing Both Sides of the Issue - Lake Trout Suppression and Rehabilitation

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Some Animals Are More Equal than Others: Keystone Species and Trophic Cascades

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The short film opens with two questions: "What determines how many species live in a given place? Or how many individuals of the species can live somewhere?" The research that provided answers to these questions was set in motion by key experiments by ecologists Robert Paine and James Estes.

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NGSS Life Sciences - Does Keystone Species Loss Impact Ecosystems?

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A *keystone species* is one that has many important interactions in an environment, despite the fact that it may have a small population size. Keystone species may make the ecosystem habitable for other organisms, even though they may not directly interact with the keystone species. Canopy-forming algae are important to shoreline ecosystems around the world.

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NGSS Life Sciences - What Causes Stability and Change in Ecosystems?

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Ecosystems regularly go through alternating periods of stability and change. There are many factors which trigger a stable ecosystem to change, and the effects of these changes ripple through every aspect of the ecosystem. Eventually, a changing ecosystem will stabilize, usually as a result of one key factor within it stabilizing, which causes the other parts of the ecosystem to stabilize as well.

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In 1966, a professor of zoology Robert T. Paine carried out a research of species inhabiting a rocky shore in California. In his experiment he removed the top predator species - sea stars - from one section of his research plot. What he witnessed after changed our understanding of the ecosystem functioning.

With the sea stars gone, almost half of other species gradually vanished, causing the collapse of the entire ecosystem. With this finding, the professor Paine discovered that some species have a larger effect on their environment than other species, regardless of their numbers. Such species are called "keystone species."

Why are keystone species important for the environment?

The importance of keystone species lies in the way they affect other organisms in the ecosystem. According to Paine's description, their presence is crucial for maintaining numbers and diversity of other species, which makes their role exceptional in the ecosystem [1].

The removal of a keystone species from an ecosystem triggers a set of negative changes. One such example is the overpopulation of one species, which leads to disappearance of other species.

One well-documented case of such a chain of events was the elimination of wolves from the Yellowstone National Park at the beginning of the last century. The negative effect on the national park's biodiversity was so profound that authorities have taken steps to introduce this keystone predator back.

While the decline of species in some remote ecosystems may not seem to be a reason for concern, the loss of biodiversity can have far-reaching implications.

For example, a reduction of species diversity can be the first step to start extensive soil erosion, eventually leading to desertification that could extend far beyond their territory.

Now that you know what is a keystone species and its importance in the ecosystem, let's have a look at some keystone animals and plants that have a great impact on their environment.

12 important examples of keystone species

Keystone species often dominate the attention of ecologists and policy-makers, who develop specific strategies for their protection, while media repeatedly report on their conservation status. Many of you have probably heard of them and perhaps wondered why these species get more attention compared to others.

As the examples below illustrate, in many cases the reason is that those species provide unique services to us and our environment.

African elephants - The oblivious creators

Elephants could be called engineers of African savanna. These great giants are a keystone species because of their ability to completely transform a landscape, bringing a variety of life alongside with them.

They shape their environment by pushing down trees, and eating small shrubs, such as acacia, creating and maintaining Africa's iconic grasslands. This sustains grazing animals such as antelopes and zebras, as well as smaller animals such as mice that burrow in the warm, dry soil of the savanna. It also enables large predators like lions to have a bounty of prey to hunt [2].

It may seem that elephants leave behind a path of destruction by creating corridors through woodlands and digging deep holes in the dry river beds, but both of these actions are highly beneficial. Corridors prevent the spread of wildfires and deep holes collect water for other animals.

Elephants are important for people as well (not for ivory). In fact, they save lives!

They are vital distributors of seeds from the Balanite tree. Many parts of this tree are used as famine food in some regions of Africa. Under normal conditions, just a fraction of seeds (less than 15 percent) turns into mature trees, but seeds digested by elephants are 50 percent more likely to start growing [3].

Sadly, elephants an iconic keystone species of African savanna are also on the list of endangered species, possibly facing extinction as soon as 2025. To learn more about the reasons of their endangerment and actions that could be taken to reverse their loss, visit our article: " Why Are Elephants Endangered Species? ".

Grizzly bears - The diligent gourmets

The main reason why grizzlies are on the list of keystone animals is because they enrich the forest floor with nutrients from salmon carcasses. When bears feed on salmon, they often drag fish deep into the forest. Leftover carcasses from their grand feast fertilize forest soil with nitrogen and phosphorus, and support growth of strong and healthy trees.

On contrary to their reputation of a scary predator, the role of grizzlies in their ecosystem is more of a gardener. When digging for roots and bulbs to eat, bears turn over large areas of soil in mountainous terrain. This aerates soils and mixes in organic material, enhancing growth of many different wildflowers. Additionally, numerous seeds of berries and pine nuts get distributed through their feces [4].

Grizzlies also regulate the numbers of several prey species, like moose and elk. They maintain healthy populations of these species by hunting the weak individuals, or scavenging on carcasses and "cleaning" up the forest.

Sharks - The cleaning commando

For the past 400 million years, the ocean health has depended on sharks more than on any other marine predator. Sharks prey on the sick and weak members of other fish populations, and some also scavenge the sea floor to feed on dead carcasses. As such, their feeding habits help prevent the spread of diseases and regulate the size of fish populations [5].

Without sharks, the whole marine ecosystem would get out of balance, as some species would overpopulate and outcompete other, possibly even driving them to extinction. So despite their bad reputation, sharks as a key predator are actually the most important keystone species in the ocean.

Sea otters - The underwater forest rangers

This second smallest marine mammal that inhabits the waters of the Pacific Northwest is the key to stabilizing the coastal marine ecosystem. More specifically, sea otters feed on sea urchins, and in doing so, they control their population.

If urchin populations grew too large, they would eat the kelp that grows in the same habitat. Kelp - a giant seaweed - is a major source of food and shelter for numerous other species, such as crabs, snails, and geese. Many fish species also use kelp forests as their hiding spot from predators.

Kelp forests are not only valuable for marine species but also for us. They reduce coastal erosion by slowing down the impact of water on the shore, and play a role even in the mitigation of climate change, as their capacity to absorb carbon dioxide is astounding. According to scientists, healthy kelp forests sequester billions of kilograms of carbon from the atmosphere.

Krill - The nutrient couriers

Krill is a nice example that size does not always matter when it comes to being a keystone species. Even at the bottom of the food chain, krill has an irreplaceable role in the marine ecosystem as a carrier of nutrients.

These tiny crustaceans feed on phytoplankton, which is incredibly rich in life-promoting nutrients such as amino acids, antioxidants, carotenoids, bioflavinoids and omega-3,6 fatty acids [6].

Being the staple food of a whale diet, krill becomes their essential source of these rich nutrients. And not only for whales. Krill is eaten by seals, penguins, squid, fish, and has a long history of being harvested even for human consumption, especially in Norway [7].

Beavers - Two beavers are better than one

In many areas, beavers were hunted to extinction for their fur and to prevent the alteration of the landscape, because they can quickly divert or block streams. While in the past this behavior was considered harmful, we know now that by building natural dams on rivers and creating wetlands, beavers provide habitats for other wildlife and ideal spawning grounds for numerous species of fish like trout and salmon.

In fact, without beaver dams we would not have healthy salmon populations! Beaver dams trap fine sediment, letting only clean water pass through, which creates perfect conditions for salmon eggs downstream.

The service beavers do for the environment does not end with providing suitable habitat to other species. It is also the creation of wetlands that has an incredible value. Wetlands play a critical role in naturally removing pollutants from water and absorbing carbon more effectively than forests.

So, it seems that unlike our destructive interventions into the environment, beavers actually alter the landscape to bring more life and boost ecosystem services. Perhaps we are the ones to learn from them instead of prohibiting them from doing their work.

Hummingbirds and Honey Possums - The controversial couple

What does the tiniest bird of Americas and the Australian marsupial have in common? Both are a keystone species and both are the key pollinators to the unique vegetation in their area.

In the forests of Patagonia, a hummingbird species called Sephanoides sephanoides pollinates on its own nearly 20% of the local woody flora. In fact, many plants in the area can only be pollinated by hummingbirds. If these birds disappeared, the diversity of vegetation would decline and some species would possibly go extinct [8].

Similarly, honey possums are crucial pollinators of banksia trees, bridle bush and other shrubs of kwongan - the unique eco-region in Southwest of Australia. Kwongan is one of the global biodiversity hotspots with high numbers of endemic species that are endangered by habitat loss. While feeding on nectar, honey possums collect pollen on their snouts and carry it to other plants. The possum foraging activity secures healthy re-growth of vegetation, and therefore, protects this rare habitat for other animal species [9,10].

Parrotfish - The coral reef janitors

Parrotfish is one of the main caretakers of coral reefs. Every day this fish visits coral reefs and feeds on algae and coral branches, removing dead pieces and cleaning the coral surface. In fact, a single fish can consume up to 4,500 kg of material every year [11]. By being such a good eater, parrotfish prevents algal proliferation in the reefs.

It is very important to keep algae species at check, because once algae dominate the reef, the healthy balance of coral reefs is irreversibly disrupted [12]. Under extreme conditions, invasive algae might even kill corals, destroying the habitat of nearly 25 percent of all marine species [13].

Prairie dogs - The lifestyle influencers

Like the elephants in savanna, prairie dogs shape the face of prairie by affecting the plant composition and distribution of water in the landscape.

Being herbivores, prairie dogs feed on grasses and they do an amazing job in trimming them down. This allows other plant species to share the same habitat. Higher plant diversity attracts various insects, birds and wildlife.

Prairie dogs even alter the water cycle in dry conditions. When keeping the vegetation low, the plant surface from where water evaporates during hot days is reduced. Lower amount of water lost through evaporation equals more moisture in the soil and the area remains greener for longer periods of time.

The network of burrows that prairie dog colonies create also serves multiple purposes. It encourages water infiltration into underground aquifers, aerates soils, distributes nutrients and even provides shelter to other small wildlife [14].

African termites - The quiet skyscraper builders

These seemingly unimportant insects have some surprising characteristics. Did you know that some of the termite mounds reach as high as 30 meters and can be over 60 years old? Some animals even take advantage of the termite homes to raise their young because of the safety they offer. For example, mongoose and barbets build their nests inside.

Termite mounds are not only attracting free tenants, they also offer nutritionally rich ground for many plant species, even trees. According to scientific observations, Acacia trees are more likely to reproduce when in proximity to termite mounds. It is because the mounds contain high levels of nitrogen, phosphorus and important micronutrients such as iron or zinc [15].

So, it may not be directly the termites themselves who draw the diverse life in savanna together, but their mound building activity and nutrient accumulation certainly does.

Woodpeckers - The bird carpenters

Woodpeckers, also referred to as tree surgeons, live mostly a solitary life, but through their hard work they affect many other species. By excavating holes in trees, they create nests for numerous animals like bats, small owls, swallows, wood ducks and many more. All these creatures are dependent on woodpecker activity because they cannot make holes in hard tree trunks on their own. Abandon woodpecker nests provide much safer and sturdier shelter to them when compared to naturally created openings in trunks.

Besides "building" cozy accommodation units for other forest dwellers, woodpeckers also control insect populations. Their beaks can reach larvae in places other birds cannot access, and once they are finished scavenging, the excavated dents in wood leave remaining prey exposed to other species.

Woodpeckers are truly important for the health of the forest all year long, as they feed on some of the most destructive forest pests such as bark beetles and wood-boring beetles, and since they are not migratory, they keep populations of these pests at check even during the long winter months [16].

Saguaro cactus - More than just a western movie background

Who would have guessed that a cactus plant mostly connected with the popularized images of desert landscape actually sustains a lot of lives?

Saguaros, the tallest plants of the desert, offer perfect nesting opportunity for many birds. Bigger birds, such as red-tailed hawks, nest between branches, and smaller ones such as gila woodpeckers, purple martins, and elf owls create nests inside the fleshy stem.

At the same time, the juicy fruits of this plant ripen during the dry summer months and become the only moist food source for animals in that time of the year [17].

There are more...

The last example of saguaro cactus as a keystone plant in the desert is just a tiny tap into the world of keystone food resources.

If you want to learn more about keystone foods, have a look at this article, which describes why sugar maple trees and figs make the top of the list as irreplaceable food sources of their ecosystems.

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12 Examples of Keystone Species | Greentumble

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In 1966, a professor of zoology Robert T. Paine carried out a research of species inhabiting a rocky shore in California. In his experiment he removed the top predator species - sea stars - from one section of his research plot. What he witnessed after changed our understanding of the ecosystem functioning.

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Some animals are more equal than others: Video 

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Some animals are more equal than others: Video 

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Some Animals Are More Equal than Others: Keystone Species and Trophic Cascades

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Doug Smith doesn't remember the moment he realized that a serious ecological crisis was under way in Yellowstone National Park. But as more and more birds began to dwindle, what appeared before him was, he says, "an expanding picture of avian collapse."

One of the first signs Smith spotted presented itself on the normally tranquil Riddle Lakein 2014. There, floating upside down, was a young trumpeter swan killed by a bald eagle. The cygnet was the last of an entire clutch of five siblings eaten by the mighty white-crowned raptors, an act that in one fell swoop wiped out all of the park's newborn swans for the year.

Smith discovered other grim clues while paddling a canoe across the southern reaches of Yellowstone Lake. Littering the glassy surface were patches of waterfowl feathers. Eagles were attacking entire flocks of ducks. They also tore apart and ate double-crested cormorants and American white pelicans.

While an obvious next step would be to look toward the sky for answers, culprits in this whodunit can actually be found up and down the food chain. Swapping out and replacing just one fish species for another has set off a chain of events negatively impacting bears, eagles, ospreys, and more-and, in turn, spelling bad news for many of the park's birds. (See more in a special issue of National Geographic devoted to Yellowstone.)

"For all of the attention that gets paid to this park's geothermal features and its famous large mammals, what we're seeing with birds is as dramatic as anything making headlines with wolves, grizzlies, and bison," says Smith, who in addition to being the park's leading wolf biologist is charged with monitoring its winged denizens.

"We could be witnessing the complete elimination of some nesting bird species in Yellowstone," he says.

Food-Chain Chaos

Along with swans, pelicans and cormorants, Smith adds loons, California gulls and Caspian terns to a list of birds being pressed to the edge of survival in Yellowstone. Some of them could soon vanish from the nation's most iconic nature preserve. (Watch: " Revealing the Secret World of Yellowstone's Wildlife.")

Three converging forces have set off a lethal chain reaction: the rippling impacts of an exotic fish-lake trout-that have decimated what used to be the last major stronghold for native Yellowstone cutthroat trout; climate change altering habitat; and humans haphazardly displacing sensitive species.

It's a jarring glimpse, Smith says, into the challenges facing natural systems once thought stable. Native species that evolved in certain places are getting interrupted, pushed around, and sometimes eliminated. "The world as we've known it is being transformed. And if it's happening in Yellowstone, it is happening everywhere," Smith says.

After wolves were restored to Yellowstone in the mid 1990s, the park was touted as the vanguard for an intact, fully functioning ecosystem with every major species present that was there when Europeans arrived on the continent half a millennium ago. Smith says that vaunted status is in jeopardy.

Most startling is the broad pattern of "ecological mayhem" playing out at Yellowstone Lake, one of the largest high-elevation freshwater lakes in the world and the liquid centerpiece of the park. The lake is an important reservoir for the namesake Yellowstone cutthroat trout ( Oncorhynchus clarkii bouvieri), but calamity ensued after exotic lake trout ( Salvelinus namaycush) somehow found their way into its waters 25 years ago, park officials say.

Lake trout, being voracious, deep-water-dwelling fish eaters, reduced cutthroat trout numbers by 90 percent. Todd Koel, Yellowstone's lead fisheries biologist and author of a science assessment, wrote that in 1998 alone, the estimated 125,000 lake trout consumed between three million and four million cutthroat trout.

That, Koel and Smith say, represented the first of several dominos to fall.

With cutthroats barely hanging on and no longer spawning in more than 60 tributary streams, their absence in turn affected species that relied on them for sustenance, including grizzly bears, especially females with cubs in early summer.

Anecdotal evidence suggests that some hungry bears shifted their summer hunting to elk calves. Grizzlies now take more young elk than wolves do. River otters, too, were affected by having fewer cutthroat trout. (Exclusive video:'Bear Bathtub' Caught on Camera in Yellowston e.)

Yet Smith says the biggest cause-and-effect correlation has involved 16 species of fish-eating birds. In the early 1990s there were 62 osprey nests documented on Yellowstone Lake, with 67 fledglings in the summer of 1994. In 2017, there were just three osprey nests and one fledgling produced.

It's important to note, perhaps, that cutthroat and lake trout are not equal; lake trout inhabit and spawn in deep lake water and are not accessible to bears and eagles the way cutthroat are.

Osprey are exclusively fish eaters, so they went elsewhere. Bald eagle nests, meanwhile, also declined around Yellowstone Lake, but they are formidable predators, and opportunistic ones.

After cutthroat trout numbers fell, eagles simply turned their hunting from fish to other birds. Yellowstone Lake has small colonies of California gulls, American white pelicans, double-crested cormorants and Caspian terns on nubs of sand and rock such as the Molly Islands in Yellowstone Lake.

Eagle predation and unusual weather in late spring have taken a huge toll, Smith says. In 1990, there were 28 nesting pairs of Caspian terns on the Molly Islands but no nests since 2005 and no reproduction of California gulls.

Eagles also have been observed attacking adult loons and targeting young swans at Riddle Lake-one of just two locations where breeding pairs of trumpeters have successfully nested.

Goosing the Numbers

On top of that, still another complication. In recent years, Canada geese have proliferated in Yellowstone, their young a bounty for growing numbers of eagles, which ultimately eat other vulnerable birds.

The last thing Yellowstone managers are going to do is lethally control numbers of geese and bald eagles, the latter being America's national avian symbol and ironically a bird that not long ago nationwide was on the federal Endangered Species list.

Loons are another iconic species, and in Greater Yellowstone the number of loons has declined by 50 percent since 1990. Just 18 breeding pairs remain in Wyoming, 70 percent of those in Yellowstone and nine loonlets fledged two years ago.

Loons have been beset by human disturbance, eagle depredation and by abnormally high water-due to precipitous snowmelt in the spring- swamping their nests.

Trumpeter swans and loons contribute much to the wild ambiance of Yellowstone, Smith says. Snow-white trumpeters have the largest wing span of any bird in North America and are known for their grace in flight and on the water. With loons, their haunting crepuscular trills are as primordial as any howling lobo.

Fishing for a Way Out

The conundrum now before Yellowstone is deciding when-and if- to intervene, Smith says.

For the last decade, Yellowstone, along with crucial funding from the park's non-profit partner, Yellowstone Forever, along with Trout Unlimited and other conservation groups, have poured millions of dollars into gill-netting lake trout to reduce their numbers and allow cutthroat trout to recover. (Watch video of a trout mating frenzy in Yellowstone.)

Eradicating lake trout entirely is impossible, but millions of the hulking fish have been taken. Koel says cutthroat losses have stabilized, though it could take many years-if ever-before their numbers are high enough to once again support other species as a food source.

"The rule of thumb we use is if impacts are natural, then we leave things alone. But if something is human-caused, then we will take action to provide remedies to problems," Smith says. "Introduction of an exotic species is an example of that; so is human use and climate change."

Yellowstone's mission is to protect park wonders, but if climate change has a deleterious effect on species, it could result in managers having to perpetually try to mitigate harmful impacts-a radical departure from current protocol that favors "letting nature take its course."

"If you start to intervene, where do you stop?" Smith asks. "Do you always know what you are doing? And if you choose not to get involved and species disappear, can you live with inaction?"

In 2011, when just five swans remained, Yellowstone convened a meeting of national experts to advance recommendations for how to save the resident population, warning that extirpation appeared to be imminent.

One of the experts was Ruth Shea. As director of a research effort called Northern Rockies Trumpeter Swan Stewards, Shea is recognized as "the grand dame" of swan conservation in the Greater Yellowstone Ecosystem, having begun her conservation work in 1976.

While she wants to be hopeful, the odds against Yellowstone's swans are overwhelming, she told National Geographic.

Historically, when trumpeter swans continent-wide were pushed to the precipice of extinction by market hunters who killed them for their meat and feather plumes, Yellowstone was a last refuge.

"It's a sad day to think the very place that saved them is struggling to keep them alive," Shea says. "It's not devastating biologically because swan numbers outside the park are increasing, but symbolically it reveals the challenges our most iconic parks are under."

Yellowstone, she notes, is confronting a constant onslaught of human recreation pressure brought by groups and individuals that want more access, not less. This at a time when the park is setting new records for visitation almost every year.

Yet putting putting some areas off-limits might be what the swans need. Shea notes that a field report from as far back as the 1930s documented that human presence can drive sensitive swans from nests.

To try improving their chances, Yellowstone has installed artificial nesting platforms for both swans and loons. Researchers have also tried "grafting," hatching swan cygnets at a lab and putting them in wild nests with the hope they'll be adopted. It has worked in some cases.

Swans are long-lived, and the number of permanent residents in the park now numbers in the mid-twenties, but successful breeding remains elusive. For the second year in a row, Smith said, following an aerial survey a few weeks ago, no new cygnets are being produced.

On top of that, pressure from eagles gives the birds a thinner margin. "When your population is reduced to handfuls of reproducing birds and even a smaller number of breeding pairs, it doesn't take the loss of many before death outpaces reproduction, and eventually they just wink out," Smith said.

When a species disappears from its homeland, the loss goes far beyond lost photo opportunities. "Every species makes its contribution to a richness whose worth cannot be calculated," Smith says.

John Muir famously observed, "When we try to pick out anything by itself, we find it hitched to everything else in the Universe." Aldo Leopold, America's forerunning ecological thinker, added half a century later in his classic A Sand County Almanac, that "to save every cog and wheel is the first precaution of the intelligent tinkerer."

The point is that, in nature, everything is interconnected. Smith says the irony is that Yellowstone has been an exemplar of that ideal, but it might also become a case study in how things can fall apart.

The birds of Yellowstone carry knowledge passed along over millennia, from one generation to the next. It includes fine-tuned courses of migration that enable them to travel thousands of miles between their summer breeding grounds in Yellowstone and winter habitat around Baja, Mexico, or the Gulf; the accrued, hard-learned lessons of where to feed and successfully nest; and how to outwit predators.

"Once that kind of intelligence is lost, it's incredibly hard to bring it back again, if you ever can," Smith says.

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Iconic Birds of Yellowstone Face Collapse-Thanks to a Fish

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Doug Smith doesn't remember the moment he realized that a serious ecological crisis was under way in Yellowstone National Park. But as more and more birds began to dwindle, what appeared before him was, he says, "an expanding picture of avian collapse." One of the first signs Smith spotted presented itself on the normally tranquil Riddle Lakein 2014.

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THE IMPACT OF REMOVING A KEYSTONE SPECIES

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"Tide Shifts Against the Concept of Keystone Species" 

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"Tide Shifts Against the Concept of Keystone Species" 

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Starfish challenge a key ecological concept, ushering in a slightly-more democratic era for tide pools everywhere

smithsonian.com

This article is from Hakai Magazine, an online publication about science and society in coastal ecosystems. Read more stories like this at hakaimagazine.com.

Sarah Gravem has become an expert at finding the small, private, nocturnal sea star Leptasterias in Pacific Coast tide pools. The trick is not to look for the sea stars, she says, but to think like their nearly blind sea snail prey, and act accordingly. "I call it snail Braille," she says. "I wasn't looking, I was feeling. I had my tide pools, I knew where [the sea stars] liked to be in the tide pools and where they liked to hide, and I just felt for them in the cracks."

Once you notice the Leptasterias, Gravem says, you notice that there are sometimes quite a lot of them-hundreds or even thousands of the sea stars in one small site. As she spent more time in the tide pools, Gravem realized that Leptasterias might have a bigger influence on coastal life than their diminutive size and relative anonymity suggest. She dug deeper into this idea, first as a graduate student at the University of California Davis-Bodega Marine Lab, and later as a postdoctoral researcher at Oregon State University. What she found might knock some of the luster off an iconic predator, and reveals the surprisingly complicated understory of one of the most cherished ideas in ecology.

In 1969, ecologist Robert Paine-who passed away June 13-laid out his keystone species hypothesis. Based on his observations in the tide pools of Mukkaw Bay, Washington, Paine argued that the charismatic ochre sea star, Pisaster ochraceus, played a crucial role in controlling the tide pool ecosystem. When Paine removed Pisaster from tide pools, mussels quickly overran the site, crowding out other species and establishing a monoculture. He realized that Pisaster had an effect disproportionate to its abundance in keeping the tide pool ecosystem in balance-an insight that, over the last half-century, has been applied far beyond the coast.

Paine spent his professional life elaborating on the complex web of life in the tide pools in Mukkaw Bay. Within months of coining the keystone hypothesis, he wrote a second paper on the interaction between Pisaster and the black turban snail, Tegula funebralis. Paine suggested that the snails' size and distribution were controlled by their "major predator," even though snails weren't Pisaster's favorite (or even second-favorite) food. Scientists and journalists alike have since referred to Pisaster as the dominant carnivore shaping the size, distribution and abundance of Tegula in a tide pool.

To Gravem, it seemed that Paine and others might have overlooked the less-charismatic sea star hiding in the back of the tide pool. She was sure Pisaster was not controlling the sea snail population in the same way it controlled the mussels, but she didn't necessarily have a replacement predator in mind, either. That is, until 2010, when an algal bloom caused Leptasterias to disappear from the tide pools she studied, and the Tegula population doubled. The next year, wasting disease struck Pisaster, and the snail population in her study area was scarcely affected.

"When we go out and see this giant Pisaster, it seems like it must be super important," Gravem says. "But if you were a snail and you had one giant Pisaster around and hundreds of tiny Leptasterias, you'd be worried about the hundreds."

Paine's keystone species hypothesis has yielded considerable insight into how ecosystems work. But several decades of follow-up work in other tide pools has shown that even the iconic Pisaster-mussel relationship is only relevant some of the time. Gravem's discovery that Leptasterias sea stars control Tegula sea snails-not Pisaster -is a cautionary tale about assuming that a species that controls one important prey controls everything else. Even more, it reinforces the idea that, in ecology, context matters.

If Pisaster is the king of the intertidal, then Gravem is part of a community of ecologists who are writing its Magna Carta: the conditions under which the keystone predator rules.

Over the past four decades, for example, Gravem's postdoctoral advisor, Oregon State ecologist Bruce Menge, has found that while Pisaster tends to rule freely on exposed coastal sites like the one Paine studied in Washington, the sea star's influence is less pronounced in more sheltered areas. The keystone species' controlling effect is prey dependent-there have to be enough mussels-and Pisaster population dependent-there have to be enough sea stars. It is size dependent, and probably temperature dependent as well. Menge has looked at sites up and down the Oregon coast, which allows him to study the effects that changing ocean conditions have on keystone relationships.

"Paine basically spent his entire career studying one location," Menge says. "The insights resulting from that were awesome, and the depth of understanding is awesome. But it's one site."

As the evidence builds, researchers like Gravem and Menge are devising a refined keystone hypothesis, one that's less rigidly hierarchical than the original. They see a habitat like the rocky tide pools of North America not as a stone archway held together by one critical species, but as a mosaic of interlocking dependencies.

"We make these nice definitions that help us explain the natural world, and the thing about ecology is that it's never black and white," Gravem says. "Keystone is useful because it's true a lot of the time. And it makes us think about the grander idea that we can have one species that's really having big domino effects on everything else. That's what Paine's real legacy is. Not that Pisaster are important. It's that predators can shape the world around them."

Read more coastal science stories at hakaimagazine.com.

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Tide Shifts Against the Concept of a Keystone Species

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smithsonian.com This article is from Hakai Magazine, an online publication about science and society in coastal ecosystems. Read more stories like this at hakaimagazine.com. Sarah Gravem has become an expert at finding the small, private, nocturnal sea star Leptasterias in Pacific Coast tide pools.

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Abstract

Coextinction models are useful to understand community robustness to species loss and resilience to disturbances. We simulated pollinator extinctions in pollination networks by using a hybrid model that combined a recently developed stochastic coextinction model (SCM) for plant extinctions and a topological model (TCM) for animal extinctions. Our model accounted for variation in interaction strengths and included empirical estimates of plant dependence on pollinators to set seeds. The stochastic nature of such model allowed us determining plant survival to single (and multiple) extinction events, and identifying which pollinators (keystone species) were more likely to trigger secondary extinctions. Consistently across three different pollinator removal sequences, plant robustness was lower than in a pure TCM, and plant survival was more determined by dependence on the mutualism than by interaction strength. As expected, highly connected and dependent plants were the most sensitive to pollinator loss and collapsed faster in extinction cascades. We predict that the relationship between dependence and plant connectivity is crucial to determine network robustness to interaction loss. Finally, we showed that honeybees and several beetles were keystone species in our communities. This information is of great value to foresee consequences of pollinator losses facing current global change and to identify target species for effective conservation.

Introduction

Anthropogenic disturbances, such as habitat transformation, climate change or biological invasions, are at present main drivers of species loss and disruption of ecological interactions. Ecological interactions among species are an important component of biodiversity because they provide relevant functions for populations, communities and ecosystems, such as pollination services. For that reason, predicting responses of ecosystems and tolerance of species to disturbances is a key issue in ecology.

The extinction of a species inevitably causes the extinction of interactions, which in turn can trigger additional extinctions of species. Models with ecological interaction networks constitute a useful tool to simulate coextinction cascades, with the ultimate goal of understanding community robustness to species loss and resilience7,8,9,10. Topological coextinction models (TCMs) represented the first attempt to explore patterns of extinction in plant-pollinator networks7. Nevertheless, these models are mainly based on static network structure and have several important constraints. For instance, they assume that a species can only become extinct when all its interacting partners are lost; however, the primary loss of a pollinator species in real plant-pollinator networks may cause the coextinction of a plant, leading in turn to the coextinction of other pollinators that strongly depended on that plant, and even to the indirect coextinction of other plants which rely on those pollinators. TCMs also neglect interaction strength heterogeneity, assuming that after the loss of a species, all its partners are equally likely to coextinction; nevertheless, pollination interactions differ in terms of quantity and quality effects and thus the coextinction probability of a species partner varies depending on the ecological effect of the lost interactions, i.e., on its interaction strength13, 14. Still, TCMs ignore that species vary greatly in their degree of functional dependence on mutualistic partners. For instance, in plant-pollinator networks, the plant breeding system is a key determinant of its dependence on pollinators to produce seeds and may modulate plant vulnerability to pollinator loss15. This dependence varies from high in plants with obligated cross-pollination to low in plants with autonomous self-pollination16. Thus, it seems crucial to take into account such dependence when modelling species vulnerability to coextinction.

Recently, a simple stochastic coextinction model (SCM) has been developed17 that simulates species extinction cascades in mutualistic networks accounting for variation in interaction strengths and species dependence on the mutualism, thus relaxing the assumption that coextinctions require the loss of all partners. Simulations assumed three categories of dependence on the mutualism (low, intermediate or high)17 due to the lack of empirical quantitative dependence estimates. More complex extinction cascades were obtained with this SCM than with TCMs and, unexpectedly, more coextinctions were found in highly connected networks.

In this study, we simulated pollinator extinctions in pollination networks and modelled coextinctions by using a hybrid model that combined the SCM17 for plant extinctions and the TCM for animal extinctions. We used, for the first time, empirically-measured values of plant dependence on pollinators (IPD, hereafter; see methods to know how it was calculated) from two plant communities to estimate plant survival probability and robustness under three different extinction scenarios (pollinator removal sequences). We then compared our findings with those using TCMs. Moreover, we wanted to assess the relative importance of incorporating estimates of plant dependence on pollinators and heterogeneity in interaction strengths when simulating species extinctions. Still, we aimed at identifying the plant species that are more sensitive to pollinator extinctions and which pollinator losses cause the highest number of plant coextinctions.

Results

Plant robustness estimated with our hybrid model was significantly lower than with the TCM (ANOVA F 1,72 = 58.03, p < 0.001; Fig. 1) in both study communities. This result was consistent regardless of the pollinator extinction scenario simulated (Supplementary Fig. S2). Specifically, the discrepancy in robustness between the two types of models was larger for highly connected and highly dependent plants on pollinators (Supplementary Fig. S3). TCM tended to overestimate robustness for generalist plant species, but to underestimate robustness for plants with a low dependency on animal pollinators.

Figure 1

Plant robustness. Mean and 95% confidence intervals of plant robustness estimated both with the topological coextinction model (TCM) and the stochastic coextinction model (SCM) in the two communities (SB: Son Bosc, PM: Puig Major). Data correspond to the random extinction scenario. In each community, confidence intervals do not overlap and plant robustness with the SCM was lower than with TCM.

When comparing the different model variants of SCM under the random extinction scenario, we found that models not incorporating plant dependence on pollinators (models D and DH; see methods) led to greater extinction cascades and smaller fractions of surviving species than models considering plant dependencies (models F and H; see methods) (Fig. 2). Consistently in the two communities, when half of the pollinators were extinct, the fraction of surviving plants was 40% in the D and DH models but c. 60% in the F and H models (Fig. 2b,d) because plants with some levels of self- or wind-pollination were able to tolerate pollinator losses. On average, 29% and 14% of plants, in the SB and the PM plant communities, respectively, survived after the extinction of all pollinators (models F and H). The lower fraction of surviving plants in PM compared to SB is probably a result of the higher overall IPD in PM (mean ± SD: 0.71 ± 0.24) than in SB (0.59 ± 0.38), although differences in average plant robustness between communities were not statistically significant ( F 1,72 = 2.47, P = 0.12). Species declines after pollinator extinctions obtained with model H, which considered dependence of plants on pollinators but simulated that all interaction strengths were homogeneous, were almost the same as those obtained with model F (Fig. 2). In addition, models D and DH, which also differed only in interaction strength heterogeneity, yielded similar results (Fig. 2). Overall, discrepancies between models show that plant dependence on pollinators is more important than interaction strength as determinants of plant species survival. Indeed, this result is supported with an analytical calculation for the random scenario. The survival probability of plant i after the removal of pollinator j is given by P ij = 1 −  IPD i d ij (see Methods). If the pollinator to be extinct is selected at random then the expected survival probability of plant i will be obtained by averaging P ij, over realizations of pollinator extinctions j, that is, P i =  P ij = 1 − 〈 IPD i d ij〉 = 1 −  IPD i/ NP, where 〈〉 is the average over realizations, and N P is the number of pollinators. For subsequent pollinator extinctions, a similar calculation leads to the result that the expected plant survival only depends on its corresponding dependence on pollinators and the specific connectivity pattern of the network (see Supplementary Information and Supplementary Fig. S1).

Figure 2

Surviving species as a function of extinction events. Fraction of surviving species ( a, c) and surviving plant species ( b, d) resulting from pollinator extinctions under the random scenario in SB (above) and PM (below) communities. Model F simulates extinctions considering the variation in both IPD (plant dependence on pollinators; see methods) and interaction strength. In model D, all plants have an IPD = 1, i.e., depend entirely on animal pollination to set seeds. Model H simulates the case in which there is no heterogeneity in interaction strength. Finally, in model DH all plants have an IPD = 1 and there is homogeneity in interaction strength. Differences between models that do not consider the real dependence of plants on pollinators (F vs. D, H vs. DH) are higher than between models that neglect interaction strength heterogeneity (F vs. H, D vs. DH). Note that the curves of the fraction of surviving species and plant species are on top of each other for Models F and H (maintaining the empirical IPD), and are also for Models H and DH (when plants depend entirely on pollinators). 95% confidence intervals are of size of the line width and are not shown for clarity.

For each simulated extinction scenario (random, generalist and specialist), as pollinator extinctions go on, a lower survival probability is observed for plants, but survival probability collapses faster if plants depend more on pollinators (Fig. 3). Plants that do not rely on pollinators for reproduction (IPD = 0) were obviously insensitive to their loss and, thus, persisted in the network even after all pollinators had disappeared. On the other extreme, plants totally dependent on pollinators (IPD = 1) never persisted regardless of the pollinator extinction scenario simulated. In both communities, an important proportion (55.5%-63.63%) of plant species was at high extinction risk, reaching survival probabilities below 0.1 during the different extinction cascades simulated. The effect of pollinator loss on plant survival was stronger under the 'generalist' simulation extinction scenario (sequential pollinator removal from the most to the least generalist) than in the 'specialist' scenario, whereas the effect was intermediate when extinctions occur randomly (Fig. 3). Plant survival probabilities decayed very fast under the 'generalist' scenario: after 5% of pollinator extinction events, plant survival probability was reduced by half for ca. 18% of plants in both communities, thus leading to a rapid species richness decline in the communities (Supplementary Fig. S4).

Figure 3

Dependence on pollinators and plant survival. Heatmaps showing the variation in plant survival probability according to plant dependence on pollinators through the cascade of extinction events under the three simulated scenarios with our full model: random extinctions, extinctions from the most to the least generalist species, and extinctions from the least to the most generalist species. In each matrix plant species (rows) were ranked by decreasing dependence on pollinators (IPD). As the extinction cascade goes on plant survival probabilities decrease, but plants with low dependencies on pollinators to set seeds (IPD → 0) tend to be more persistent that plants with a high dependence (IPD → 1) on pollinators.

Plant survival probability was strongly negatively correlated with plant dependence ( r s = −0.97, P < 0.001). Thus, plants highly dependent on pollinators became extinct before those depending little on them. Significant but lower negative correlations were also found between plant survival probabilities and plant centralities within the networks (degree: r s = −0.50, P < 0.05; eigenvector centrality: r s = −0.41, P < 0.05) suggesting a larger vulnerability to coextinction for plants with many generalist pollinators. Evenness of interactions, by contrast, was not associated to plant survival probabilities ( r s = −0.20, P  = 0.23).

Regarding pollinators' traits, species leading to more coextinctions after their primary extinction were the most generalized pollinators, i.e., those with more interactions with plants (Fig. 4; r s = −0.81, P < 0.001). The fraction of surviving plants after pollinator extinction was also negatively correlated with pollinator species strength ( r s = −0.88, P < 0.001), evenness ( r s = −0.63, P < 0.001) and eigenvector centrality ( r s = −0.61, P < 0.001). In SB community, the pollinators causing the highest number of plant secondary extinctions were two beetles ( Meligethes sp. and Spermophagus sp.) and the honeybee ( Apis mellifera). In PM, on the other hand, the three keystone pollinator species were the beetle Oedemera flavipes, a small braconid wasp ( Chelonus sp.), and the honeybee. The honeybee was, thus, identified as a keystone species in both study communities leading to the coextinction of one plant species when it disappears from the communities (1.35 and 0.88 plant species on average in SB and PM, respectively). The loss of species from other functional groups, such as flies, bee flies or butterflies, had a minimum impact on either community (Fig. 5).

Figure 4

Pollinator degree. Association between pollinator degree and the number of surviving plants after extinction of each pollinator in the two communities: ( a) Son Bosc and ( b) Puig Major. The loss of highly connected pollinator species caused the largest number of coextinctions in both networks.

Figure 5

Functional groups influence on surviving plants. Mean fraction of surviving plant species after the extinction of pollinators belonging to different functional groups. BF: bee flies, BU: butterflies, OT: others (mostly orthopterans and hemipterans), FL: flies, WA: wasps, LB: large bees, SB: small bees, HF: hoverflies, BE: beetles, AN: ants, HB: honeybee. The strength of each pollinator species is also depicted in a colour scale. The dashed lined represents the average effect of losing a single pollinator species. Data are shown for SB ( a) and PM ( b) communities. Note that the losses of species with highest strength are those causing the largest plant extinctions.

Discussion

Our study demonstrates that a key step to reach a more comprehensive understanding of species extinction risk in pollination mutualistic networks consists in incorporating real estimates of species dependence on partners into coextinction simulation models. We confirmed the finding by ref. 17 that stochastic coextinction models (SCMs) predict lower network and species robustness than topological models (TCMs). This is because complex extinction cascades can occur when relaxing the assumption that coextinctions require the loss of all partners17. Nevertheless, extinction cascades under our hybrid model are constrained to be less complex than those under the SCM of Ref. 17 because pollinators can only go secondarily extinct when their last remaining partner disappears. Therefore, incorporating real estimates of pollinators' dependence on plants might even lead to a lower robustness than the observed here. We further found that discrepancy in robustness when comparing TCMs and SCMs was larger for generalized and highly-dependent species, which corroborates that extinction cascades are more likely under high dependencies and high connectance17. The fact that highly connected communities of mutualists are more sensitive to secondary extinctions than less connected communities challenges the old idea of a positive relationship between connectance and robustness to species extinctions in ecological networks and at the same time calls for the search of mechanisms that allow species to persist in the community. Previous comparisons of simulations incorporating structural dynamics with those of static topologies in food webs showed also that species richness and connectance were uncorrelated with robustness21. In addition, our results can also be put in context of the idea of nestedness promoting stability in mutualistic networks. According to ref. 22, the species contributing most to nestedness are those also contributing most to the persistence of the community, being in turn the most vulnerable to extinction. Given that the species contributing most to nestedness tend to be highly connected species, and considering our findings that these have a lower survival probability, we predict that species contributing most to nestedness will be those less likely to survive in a cascade of co-extinctions.

One interesting finding of our model was that plant persistence in the networks showed to be more influenced by their dependence on pollinators than by the heterogeneity in interaction strengths. At least this is true when using interaction frequency as a measure of interaction strength in networks. In general, interaction frequency is considered a good proxy of the total effect of animal mutualists on plants14. However, we must note that the heterogeneity of another measure of interaction strength representing the pollination qualitative component ( e.g., frequency of pollen deposition) rather than the quantitative one might be in some cases more relevant for determining plant survival. Moreover, note also that we averaged the results of the sequence of pollinator extinctions and this decreased the impact on plant survival; if the most important pollinator was always removed first, the impact would have been certainly greater. Models that neglect dependence represent the worst-case extinction scenario because they cannot simulate the persistence of plants that can set seeds without the help of pollinators. Given that natural communities, in general, vary in plant species dependence on the mutualism15, 23, it thus seems crucial to estimate and include such variable in models when assessing the relative robustness of different mutualistic communities to species extinctions.

Due to the increasing number of anthropogenic pressures on species, it is a major challenge to identify which life history, morphological or functional traits of species in ecological networks are associated to likelihood of extinction after partner loss. Our results show that, at least for plants in pollination networks, dependence on pollinators to produce seeds is a strong correlate of plant extinction probability and determines the order at which species go extinct. Plant species with a strong dependence, such as dioecious or self-incompatible species, were more prone to coextinction after pollinator losses and disappeared first from the community. On the other hand, low-dependent plant species, such as species with autogamous pollination, facultative selfing or wind-pollination, were less vulnerable and persisted longer in communities. Moreover, other plant species traits not studied here could contribute to the vulnerability or resilience of species to coextinction24. For instance, some plant species have alternative mechanisms to ensure reproduction without pollinators, such as vegetative propagation, which may also reduce their risk of extinction16.

However, plant coextinction likelihood is not exclusively associated to plant reproductive dependence on pollinators, but also depends on their connectivity within the network. Consistently in the two communities, the most generalist plants tended to have lower survival probabilities. This is because plants with a high degree or centrality 'play the extinction lottery more times' when connected to more pollinators. Thus, generalized plant species that are self-incompatible and not wind-pollinated would be the most susceptible to pollinator losses and the first to disappear ( e.g., Lotus corniculatus, Cistus salviifolius in our communities). Interestingly, this suggests that the correlation between species dependence and connectivity in networks may be crucial to determine the robustness of entire communities to interaction loss. Communities can vary in the association between specialization level and dependence23. Although plants highly reliant on pollinators might be expected to have more interactions than less dependent species -to ensure their reproduction and buffer from fluctuations in pollinator populations-, the whole specialist-generalist gradient is found in both self-compatible and incompatible plants15, 25. Communities where the most dependent species are also highly connected species (hubs), occupying central positions in the network, would be particularly susceptible to rapid coextinction cascades.

The SCM used here only incorporates real dependence estimates for plants, but ideally SCMs should add estimates of dependence also for pollinators. These estimates could be obtained, for instance, by measuring the contribution of pollen to the pollinators' offspring26. There are pollinators that strongly depend on floral resources for survival (obligate flower-visitors) because they solely feed on pollen and nectar, whereas others are less dependent (facultative flower-visitors) as they use pollen and nectar only as a diet complement27. Moreover, there are several ecological and life-history traits of pollinators, such as nesting, sociality or body size, which likely influence their sensitivity to disturbances28. Including this type of information in future models would certainly allow making better predictions on species coextinctions in pollination networks. Indeed, this framework could be extended to other kind of networks, such as seed-dispersal, host-parasitoid or plant-plant networks.

In addition, the identification of pollinator species that are more likely to trigger secondary extinctions can help targeting conservation efforts on keystone species29. Consistently in the two communities, pollinators leading to more coextinctions after their primary extinction were generalized species, occupying central positions in the network, showing a greater species strength, as well as a high interaction evenness. The loss of generalist pollinator species with high strength is likely to cause more coextinctions because there are more and stronger pathways available for the propagation of direct and indirect effects. A recent study actually found that deletion sequences which first removed species with the largest strength led to lower food web robustness than the simple removal of hubs30. Interestingly, the managed honeybee was identified as a keystone species, playing an important role for plant persistence in both networks studied, despite it represented a relatively small fraction of total pollinator visitation (ca. 11% and 18% in SB and PM, respectively). Its potential extinction or decrease in activity patterns due to the combined effect of pathogens, predators, pesticides, lack of floral resources, etc.31 might cause secondary extinctions in pollination networks. The honeybee is widely known to be an invasive flower visitor, with high species strength, which is associated to its highly plastic behaviour, its efficient search and exploitation of resources, and its indiscriminate foraging32. The extinction of species from other functional groups showed a lower effect on plant survival, except for several species of beetles, which were also keystone species due to their ubiquity on flowers ( e.g., ref. 6).

Unfortunately, if keystone species are in turn more vulnerable to coextinction due to their higher connectance, rapid coextinction cascades could take place in communities. Previous studies22 found that strong contributors to overall community persistence are in fact the nodes most vulnerable to extinction. However, experimental manipulative studies are needed33, 34 to verify theoretical predictions made by network coextinction models on species extinction risk and community robustness. Incorporating dependence on the mutualism and exploring the relationship between connectivity and dependence arises as a key point for future studies assessing community stability.

Methods

Study sites and sampling of plant-pollinator interactions

Plant-pollinator interactions were sampled in two different communities of Mallorca (Balearic Islands): (i) a dune marshland located at sea level in the northeast of the island (Son Bosc; SB hereafter) and (ii) a high mountain shrub located at ca. 1,100 m above sea level (Sa Coma de n'Arbona in Puig Major; PM hereafter). During two consecutive flowering seasons (years 2009 and 2010, from April to July at SB and from May to August at PM) time- fixed flower visitation observations (3 min in SB and 5 min in PM) were conducted on randomly selected flowering plants. Observations were performed between 10:00 am-5:00 pm on sunny and non-windy days. We recorded the identity of insect flower-visitors that contacted flower reproductive parts (pollinators, hereafter) and the number of flower visits made by each pollinator species. Pollinators unidentified in the field were captured for further identification by specialized taxonomists and were classified into 11 pollinator functional groups: large bees (≥10 mm long), small bees (<10 mm), honeybees, beetles, flies, hoverflies, bee flies, wasps, butterflies, ants, and others. More details about sampling and pollinators observed are in ref. 23.

Flower-visitation data from both years were pooled to construct quantitative plant-pollinator networks for each study site only including species for which reproductive dependence on pollinators was studied (see next section). Interaction strength in such networks was the total number of visits per flower per hour. These networks were later used to simulate coextinction cascades.

Measuring plant reproductive dependence on pollinators

For ca. 30% of flowering plant species in each study community we estimated reproductive dependence on pollinators as the difference in seed set with and without pollinators. The study species (SB = 27, PM = 11) represented 42% and 35% of all plant families present in both communities, respectively, and included both specialist and generalist plants (from one or a few pollinators to many). When plants had flowers at bud stage, we randomly selected 3-4 plant individuals per species. On each plant we counted and marked flowering branches or pedicels to conduct two treatments: (i) open pollination (OP), i.e., flowers left to be naturally pollinated, and (ii) pollinator exclusion (PE), i.e., flowers covered with fine mesh bags preventing insect visitation but allowing pollen grains to go through, to assess the role of self-pollination and the potential effect of wind. The number of flower units marked per plant and treatment varied depending on species floral display. Plants were weekly monitored, and fruits set in each treatment were collected when nearly or fully ripe. Fruits were dissected in the laboratory and viable seeds were counted. Mean seed set ( SS) for each treatment was calculated as the total number of seeds produced per marked flower unit.

The degree of plant dependence on insect pollinators ( IPD) was estimated as the fraction of seed set attributable to pollinator interactions, i.e., the open pollination seed set after excluding the contribution of self- and wind-pollination. Thus, for each plant species we calculated IPD as I P D= S−S S =1− S S , being SS op and SS pe the mean seed set obtained in open pollination and in the pollinator exclusion treatment, respectively. Therefore, IPD ranges from 0 for plants that produce seeds independently of pollinators ( i.e., by selfing and/or wind-pollination) to 1 for plants fully relying on pollinators for seed production. For most species, IPD may be contingent upon the biotic and abiotic conditions of each particular site, and may also vary across seasons, although for other species, IPD can be considered as constant ( e.g., those that are self-incompatible and are not wind-pollinated have a consistent IPD  = 1).

The coextinction stochastic model

We adapted the recently developed stochastic simulation model for coextinctions in mutualistic networks17 that considers the intrinsic reproductive dependence of species on the mutualism and the relative frequency of each interaction between mutualistic partners (dependence sensu ref. 35).

Our model simulates species extinction cascades and begins with the removal of a pollinator species j in the network. After the primary extinction of a pollinator j, all their plant partners have a probability of survival given by P ij = 1 −  IPD i d ij, where P ij is the survival probability of plant species i following the extinction of a partner pollinator species j; IPD i is the empirical estimate of reproductive dependence on insect pollinators of plant species i ( i.e., to what extent pollinators contribute to i's seed set); d ij is defined as the fraction of all pollinator interactions involving plant i and pollinator j, and was estimated as the fraction of visits by j to i divided by the total visits of the surviving partners to i and including j itself (following refs 17 and 35). Thus, plant coextinction is more likely (small P ij) when plants strongly depend on insect pollination to set seeds and the pollinator partner lost is important in terms of interaction frequency. When secondary plant extinctions occur, they can in turn lead to new pollinator extinctions. Because empirical estimates of the reproductive dependence of pollinators on plant food resources (pollen, nectar) were not available in our study, the survival probabilities of pollinators are not calculated with the previous formula. Instead, in our model, a pollinator can only become extinct when it is left without food resources, i.e., it has lost all interacting partners. The loss of pollinators that interacted with an extinct plant therefore cannot lead to more plant extinctions. Thus, the model we used may be viewed as a hybrid version between stochastic and topological models (stochastic for plants and topological for pollinators).

When no more coextinctions occur after each primary pollinator extinction, the number of plants and pollinators remaining in the network are calculated, and a new pollinator extinction is simulated again, and so on, until no pollinators are left in the network (see pollinator extinction simulation scenarios). Note that interactions that are lost after primary extinction are not recovered after each secondary extinction step. As the extinction cascade goes on, new survival probabilities for plants are estimated each time after an extinction event by recalculating relative interaction strengths d ij. In other words, after each pollinator loss, the rest of pollinators of a given plant "are allowed" to compensate the number of visits of that lost pollinator by increasing their interaction strengths with the plant36. For example, species i has interaction strength d ij = 1 when j is its last surviving partner, regardless of the initial value of d ij. In this case, P ij = 0 when the plant fully depends on pollinators, but P ij > 0 when IPD i ≠ 1. Therefore, plant species i may persist even if it has lost all of its partners, an important difference from the static topological models. However, our model does not consider re-wiring, i.e., species cannot establish new interactions after the loss of their original mutualistic partners.

Pollinator extinction simulation scenarios

For each network, we simulated three different scenarios of pollinator species loss with our model: (1) random scenario, in which pollinator species were removed in a random order, (2) generalist scenario, in which pollinator species were sequentially removed from the most to the least connected pollinator, and (3) specialist scenario, in which pollinator species were sequentially removed from the least to the most connected. The random scenario represents a null scenario with which to compare, as done in other studies7, 20. The generalist scenario is typically used to explore the "attack tolerance" of networks to the loss of hub nodes; this scenario may occur, for instance, when super-generalist invasive species (which sometimes can be alien invasive species) are removed in communities41. Lastly, the specialist scenario is expected when weakly linked species are at greatest risk of real-world extinction. For instance, specialist pollinator species have been found to be more vulnerable than generalist ones to land-use intensification and habitat fragmentation42, 43.

The simulations of the stochastic coextinction model were implemented in FORTRAN (v. f 95). A total of 10,000 sequences of pollinator removal with no replacement were performed for each scenario. Plant survival probabilities were obtained after each extinction event (pollinator species removal) and after the extinction of all pollinators under each simulated scenario. We also calculated robustness ( R i) for plant species i as the area below the decaying curve of the survival probability of i after each pollinator extinction (measured as the fraction of extinction events relative to the total number of pollinators). Plant robustness is a quantification of plant's tolerance to pollinator loss. The value is bounded between 0, when plant survival probability decreases abruptly after pollinator extinctions, and 1, when it decreases mildly, thus indicating fragility and robustness, respectively44.

Adding complexity to coextinction simulation models

We were interested in determining how the addition of estimates of plant reproductive dependence on pollinators and quantitative interaction strengths in coextinction simulation models may affect conclusions drawn about species robustness to pollinator loss. Hence, we first compared plant robustness estimates obtained with our SCM to those obtained with TCM. Secondly, we assessed the relative importance of including dependence on pollinators and the heterogeneity of interaction strengths in our simulation coextinction model by comparing, for the random scenario, the results obtained with different variants of the SCM (F, D, H and DH). Model F corresponds to the full coextinction model, as explained above, which incorporates both empirical estimates of plant reproductive dependence on pollinators (IPD) and interaction strengths. In model D, we simulated a community in which all plant species depended entirely on animal pollination to set seeds, i.e., we assigned all species in the network an IPD i = 1, but kept observed interaction strengths. In model H, there was no heterogeneity in interaction strengths, i.e., we assigned homogeneous interaction frequencies among pollinators of plant i but maintaining IPD i to the empirical values. Finally, model DH simulated that all plants depended entirely on pollinators ( IPD i = 1) and that interaction strength was homogenous across all pollinator species of plant i. The decay in species and plant richness with pollinator loss was compared among the four model variants.

Sensitivity of plant species to pollinator loss and identifying keystone pollinators

Plant survival probability after the extinction cascade simulations gives an idea of sensitivity of plant species to loss of pollinator partners. Extinction risk is likely to depend on species traits24, 45 and network characteristics46. In order to determine which traits were associated to the sensitivity of plant species to pollinator loss, we assessed the relationship between plant survival probabilities and: (a) plant dependence of pollinators, (b) plant degree (normalised by the total number of pollinators in each network), (c) interaction evenness, and (d) eigenvector centrality scores, which measure how central is a species in the network taking into account the centrality of partner species, so that plant species that tend to interact with more generalized pollinators will have larger scores47, 48. Spearman rank correlations between variables were conducted pooling data for the two communities.

Finally, we identified pollinator keystone species in our communities, i.e., pollinators whose loss would cause more coextinctions. In order to do that, we simulated with SCM (10,000 simulations) the selective extinction of each pollinator species in our networks and compared the number of surviving plant species after pollinator removal. We then assessed whether this fraction of surviving plants was associated to: (a) pollinator degree (normalised by the number of plants in each network), (b) interaction evenness, (c) eigenvector centrality, and (d) species strength35. Spearman rank correlations between these variables were conducted.

Data Availability

The datasets analysed during the current study as well as figure source data and scripts are available in the digital.csic repository http://dx.doi.org/10.20350/digitalCSIC/8507.

Additional information

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References

1. 1.

2. 23.
Tur, C., Castro-Urgal, R. & Traveset, A. Linking plant specialization to dependence in interactions for seed set in pollination networks. PloS one 8, e78294 (2013).

3. 24.

4. 36.
Hallett, A. C., Mitchell, R. J., Chamberlain, E. R. & Karron, J. D. Pollination success following loss of a frequent pollinator: the role of compensatory visitation by other effective pollinators. AoB PLANTS 9, plx020 -plx020, doi: 10.1093/aobpla/plx020 (2017).

5. 39.

6. 45.

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Acknowledgements

We thank Rocío Castro-Urgal, Jaume Reus, Pep Mora, Joan G. Torrandell, Héctor Guerrero and Zeeba Khan for their work in the field during pollinator surveys and flower bagging experiments, and Jaume Reus, Waleska Vázquez and Clara Vignolo for helping in the laboratory counting seeds. We are also very grateful to the taxonomists that identified the collected insects: David Baldock, Xavier Canyelles, Leopoldo Castro, Andreas Werner Ebmer, Xavier Espadaler, David Gibbs, Gerard Le Goff, Jordi Ribes, Paolo Rosa and Erwin Scheuchl. This study was performed within project CGL2013-44386-P financed to AT by the Spanish Ministry of Economy and Competitiveness and project SPASIMM (FIS2016-80067-P AEI/FEDER, UE) to VME by Agencia Estatal de Investigación (AEI, Spain) and Fondo Europeo de Desarrollo Regional (FEDER).

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Affiliations

1. Institut Mediterrani d'Estudis Avançats IMEDEA (CSIC-UIB), Global Change Research Group, C/Miquel Marqués 21, E07190-Esporles, Mallorca, Balearic Islands, Spain

Anna Traveset

& Cristina Tur

2. Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), E07122, Palma de Mallorca, Spain

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Contributions

The three authors designed the study. V.M.E. developed the model and run all the simulations. C.T. and A.T. compiled the network data from our previous studies. C.T. performed the statistical analyses and drew the figures. A.T. led the writing, with substantial contributions from all authors.

Competing Interests

The authors declare that they have no competing interests.

Corresponding author

Correspondence to Víctor M. Eguíluz.

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Plant survival and keystone pollinator species in stochastic coextinction models: role of intrinsic dependence on animal-pollination

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Coextinction models are useful to understand community robustness to species loss and resilience to disturbances. We simulated pollinator extinctions in pollination networks by using a hybrid model that combined a recently developed stochastic coextinction model (SCM) for plant extinctions and a topological model (TCM) for animal extinctions.