Farming on screen

Bodies, Minds, and the Artificial Intelligence Industrial Complex, part six
Also published on Resilience.

What does the future of farming look like? To some pundits the answer is clear: “Connected sensors, the Internet of Things, autonomous vehicles, robots, and big data analytics will be essential in effectively feeding tomorrow’s world. The future of agriculture will be smart, connected, and digital.”1

Proponents of artificial intelligence in agriculture argue that AI will be key to limiting or reversing biodiversity loss, reducing global warming emissions, and restoring resilience to ecosystems that are stressed by climate change.

There are many flavours of AI and thousands of potential applications for AI in agriculture. Some of them may indeed prove helpful in restoring parts of ecosystems.

But there are strong reasons to expect that AI in agriculture will be dominated by the same forces that have given the world a monoculture agri-industrial complex overwhelmingly dependent on fossil fuels. There are many reasons why we might expect that agri-industrial AI will lead to more biodiversity loss, more food insecurity, more socio-economic inequality, more climate vulnerability. To the extent that AI in agriculture bears fruit, many of these fruits are likely to be bitter.

Optimizing for yield

A branch of mathematics known as optimization has played a large role in the development of artificial intelligence. Author Coco Krumme, who earned a PhD in mathematics from MIT, traces optimization’s roots back hundreds of years and sees optimization in the development of contemporary agriculture.

In her book Optimal Illusions: The False Promise of Optimization, she writes,

“Embedded in the treachery of optimals is a deception. An optimization, whether it’s optimizing the value of an acre of land or the on-time arrival rate of an airline, often involves collapsing measurement into a single dimension, dollars or time or something else.”2

The “single dimensions” that serve as the building blocks of optimization are the result of useful, though simplistic, abstractions of the infinite complexities of our world. In agriculture, for example, how can we identify and describe the factors of soil fertility? One way would be to describe truly healthy soil as soil that contains a diverse microbial community, thriving among networks of fungal mycelia, plant roots, worms, and insect larvae. Another way would be to note that the soil contains sufficient amounts of at least several chemical elements including carbon, nitrogen, phosphorus, potassium. The second method is an incomplete abstraction, but it has the big advantage that it lends itself to easy quantification, calculation, and standardized testing. Coupled with the availability of similar simple quantified fertilizers, this method also allows for quick, “efficient,” yield-boosting soil amendments.

In deciding what are the optimal levels of certain soil nutrients, of course, we must also give an implicit or explicit answer to this question: “Optimal for what?” If the answer is, “optimal for soya production”, we are likely to get higher yields of soya – even if the soil is losing many of the attributes of health that we might observe through a less abstract lens. Krumme describes the gradual and eventual results of this supposedly scientific agriculture:

“It was easy to ignore, for a while, the costs: the chemicals harming human health, the machinery depleting soil, the fertilizer spewing into the downstream water supply.”3

The social costs were no less real than the environmental costs: most farmers, in countries where industrial agriculture took hold, were unable to keep up with the constant pressure to “go big or go home”. So they sold their land to the fewer remaining farmers who farmed bigger farms, and rural agricultural communities were hollowed out.

“But just look at those benefits!”, proponents of industrialized agriculture can say. Certainly yields per hectare of commodity crops climbed dramatically, and this food was raised by a smaller share of the work force.

The extent to which these changes are truly improvements is murky, however, when we look beyond the abstractions that go into the optimization models. We might want to believe that “if we don’t count it, it doesn’t count” – but that illusion won’t last forever.

Let’s start with social and economic factors. Coco Krumme quotes historian Paul Conkin on this trend in agricultural production: “Since 1950, labor productivity per hour of work in the non-farm sectors has increased 2.5 fold; in agriculture, 7-fold.”4

Yet a recent paper by Irena Knezevic, Alison Blay-Palmer and Courtney Jane Clause finds:

“Industrial farming discourse promotes the perception that there is a positive relationship—the larger the farm, the greater the productivity. Our objective is to demonstrate that based on the data at the centre of this debate, on average, small farms actually produce more food on less land ….”5

Here’s the nub of the problem: productivity statistics depend on what we count, and what we don’t count, when we tally input and output. Labour productivity in particular is usually calculated in reference to Gross Domestic Product, which is the sum of all monetary transactions.

Imagine this scenario, which has analogs all over the world. Suppose I pick a lot of apples, I trade a bushel of them with a neighbour, and I receive a piglet in return. The piglet eats leftover food scraps and weeds around the yard, while providing manure that fertilizes the vegetable garden. Several months later I butcher the pig and share the meat with another neighbour who has some chickens and who has been sharing the eggs. We all get delicious and nutritious food – but how much productivity is tallied? None, because none of these transactions are measured in dollars nor counted in GDP.

In many cases, of course, some inputs and outputs are counted while others are not. A smallholder might buy a few inputs such as feed grain, and might sell some products in a market “official” enough to be included in economic statistics. But much of the smallholder’s output will go to feeding immediate family or neighbours without leaving a trace in GDP.

If GDP had been counted when this scene was depicted, the sale of Spratt’s Pure Fibrine poultry feed may have been the only part of the operation that would “count”. Image: “Spratts patent “pure fibrine” poultry meal & poultry appliances”, from Wellcome Collection, circa 1880–1889, public domain.

Knezevic et al. write, “As farm size and farm revenue can generally be objectively measured, the productivist view has often used just those two data points to measure farm productivity.” However, other statisticians have put considerable effort into quantifying output in non-monetary terms, by estimating all agricultural output in terms of kilocalories.

This too is an abstraction, since a kilocalorie from sugar beets does not have the same nutritional impact as a kilocalorie from black beans or a kilocalorie from chicken – and farm output might include non-food values such as fibre for clothing, fuel for fireplaces, or animal draught power. Nevertheless, counting kilocalories instead of dollars or yuan makes possible more realistic estimates of how much food is produced by small farmers on the edge of the formal economy.

The proportions of global food supply produced on small vs. large farms is a matter of vigorous debate, and Knezevic et al. discuss some of widely discussed estimates. They defend their own estimate:

“[T]he data indicate that family farmers and smallholders account for 81% of production and food supply in kilocalories on 72% of the land. Large farms, defined as more than 200 hectares, account for only 15 and 13% of crop production and food supply by kilocalories, respectively, yet use 28% of the land.”6

They also argue that the smallest farms – 10 hectares (about 25 acres) or less – “provide more than 55% of the world’s kilocalories on about 40% of the land.” This has obvious importance in answering the question “How can we feed the world’s growing population?”7

Of equal importance to our discussion on the role of AI in agriculture, are these conclusions of Knezevic et al.: “industrialized and non-industrialized farming … come with markedly different knowledge systems,” and “smaller farms also have higher crop and non-crop biodiversity.”

Feeding the data machine

As discussed at length in previous installments, the types of artificial intelligence currently making waves require vast data sets. And in their paper advocating “Smart agriculture (SA)”, Jian Zhang et al. write, “The focus of SA is on data exploitation; this requires access to data, data analysis, and the application of the results over multiple (ideally, all) farm or ranch operations.”8

The data currently available from “precision farming” comes from large, well-capitalized farms that can afford tractors and combines equipped with GPS units, arrays of sensors tracking soil moisture, fertilizer and pesticide applications, and harvested quantities for each square meter. In the future envisioned by Zhang et al., this data collection process should expand dramatically through the incorporation of Internet of Things sensors on many more farms, plus a network allowing the funneling of information to centralized AI servers which will “learn” from data analysis, and which will then guide participating farms in achieving greater productivity at lower ecological cost. This in turn will require a 5G cellular network throughout agricultural areas.

Zhang et al. do not estimate the costs – in monetary terms, or in up-front carbon emissions and ecological damage during the manufacture, installation and operation of the data-crunching networks. An important question will be: will ecological benefits be equal to or greater than the ecological harms?

There is also good reason to doubt that the smallest farms – which produce a disproportionate share of global food supply – will be incorporated into this “smart agriculture”. Such infrastructure will have heavy upfront costs, and the companies that provide the equipment will want assurance that their client farmers will have enough cash outputs to make the capital investments profitable – if not for the farmers themselves, then at least for the big corporations marketing the technology.

A team of scholars writing in Nature Machine Intelligence concluded,

“[S]mall-scale farmers who cultivate 475 of approximately 570 million farms worldwide and feed large swaths of the so-called Global South are particularly likely to be excluded from AI-related benefits.”9

On the subject of what kind of data is available to AI systems, the team wrote,

“[T]ypical agricultural datasets have insufficiently considered polyculture techniques, such as forest farming and silvo-pasture. These techniques yield an array of food, fodder and fabric products while increasing soil fertility, controlling pests and maintaining agrobiodiversity.”

They noted that the small number of crops which dominate commodity crop markets – corn, wheat, rice, and soy in particular – also get the most research attention, while many crops important to subsistence farmers are little studied. Assuming that many of the small farmers remain outside the artificial intelligence agri-industrial complex, the data-gathering is likely to perpetuate and strengthen the hegemony of major commodities and major corporations.

Montreal Nutmeg. Today it’s easy to find images of hundreds varieties of fruit and vegetables that were popular more than a hundred years ago – but finding viable seeds or rootstock is another matter. Image: “Muskmelon, the largest in cultivation – new Montreal Nutmeg. This variety found only in Rice’s box of choice vegetables. 1887”, from Boston Public Library collection “Agriculture Trade Collection” on flickr.

Large-scale monoculture agriculture has already resulted in a scarcity of most traditional varieties of many grains, fruits and vegetables; the seed stocks that work best in the cash-crop nexus now have overwhelming market share. An AI that serves and is led by the same agribusiness interests is not likely, therefore, to preserve the crop diversity we will need to cope with an unstable climate and depleted ecosystems.

It’s marvellous that data servers can store and quickly access the entire genomes of so many species and sub-species. But it would be better if rare varieties are not only preserved but in active use, by communities who keep alive the particular knowledge of how these varieties respond to different weather, soil conditions, and horticultural techniques.

Finally, those small farmers who do step into the AI agri-complex will face new dangers:

“[A]s AI becomes indispensable for precision agriculture, … farmers will bring substantial croplands, pastures and hayfields under the influence of a few common ML [Machine Learning] platforms, consequently creating centralized points of failure, where deliberate attacks could cause disproportionate harm. [T]hese dynamics risk expanding the vulnerability of agrifood supply chains to cyberattacks, including ransomware and denial-of-service attacks, as well as interference with AI-driven machinery, such as self-driving tractors and combine harvesters, robot swarms for crop inspection, and autonomous sprayers.”10

The quantified gains in productivity due to efficiency, writes Coco Krumme, have come with many losses – and “we can think of these losses as the flip side of what we’ve gained from optimizing.” She adds,

“We’ll call [these losses], in brief: slack, place, and scale. Slack, or redundancy, cushions a system from outside shock. Place, or specific knowledge, distinguishes a farm and creates the diversity of practice that, ultimately, allows for both its evolution and preservation. And a sense of scale affords a connection between part and whole, between a farmer and the population his crop feeds.”11

AI-led “smart agriculture” may allow higher yields from major commodity crops, grown in monoculture fields on large farms all using the same machinery, the same chemicals, the same seeds and the same methods. Such agriculture is likely to earn continued profits for the major corporations already at the top of the complex, companies like John Deere, Bayer-Monsanto, and Cargill.

But in a world facing combined and manifold ecological, geopolitical and economic crises, it will be even more important to have agricultures with some redundancy to cushion from outside shock. We’ll need locally-specific knowledge of diverse food production practices. And we’ll need strong connections between local farmers and communities who are likely to depend on each other more than ever.

In that context, putting all our eggs in the artificial intelligence basket doesn’t sound like smart strategy.

Notes

1 “Achieving the Rewards of Smart Agriculture,” by Jian Zhang, Dawn Trautman, Yingnan Liu, Chunguang Bi, Wei Chen, Lijun Ou, and Randy Goebel, Agronomy, 24 February 2024.

2 Coco Krumme, Optimal Illusions: The False Promise of Optimization, Riverhead Books, 2023, pg 181 A hat tip to Mark Hurst, whose podcast Techtonic introduced me to the work of Coco Krumme.

3 Optimal Illusions, pg 23.

4 Optimal Illusions, pg 25, quoting Paul Conkin, A Revolution Down on the Farm.

5 Irena Knezevic, Alison Blay-Palmer and Courtney Jane Clause, “Recalibrating Data on Farm Productivity: Why We Need Small Farms for Food Security,” Sustainability, 4 October 2023.

6 Knezevic et al., “Recalibrating the Data on Farm Productivity.”

7 Recommended reading: two farmer/writers who have conducted more thorough studies of the current and potential productivity of small farms are Chris Smaje and Gunnar Rundgren.

8 Zhang et al., “Achieving the Rewards of Smart Agriculture,” 24 February 2024.

9 Asaf Tzachor, Medha Devare, Brian King, Shahar Avin and Seán Ó hÉigeartaigh, “Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities,” Nature Machine Intelligence, 23 February 2022.

10 Asaf Tzachor et al., “Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities.”

11 Coco Krumme, Optimal Illusions, pg 34.

Image at top of post: “Alexander Frick, Jr. in his tractor/planter planting soybean seeds with the aid of precision agriculture systems and information,” in US Dep’t of Agriculture album “Frick Farms gain with Precision Agriculture and Level Fields”, photo for USDA by Lance Cheung, April 2021, public domain, accessed via flickr. 

Reckoning with ‘the battering ram of the Anthropocene’

Also posted on Resilience

Is the word right on the tip of your tongue? You know, the word that sums up the ecological effects of more, faster and bigger vehicles, driving along more and wider lanes of roadway, throughout your region and all over the world?

If the word “traffication” comes readily to mind, then you are likely familiar with the work of British scientist Paul Donald. After decades spent studying the decline of many animal species, he realized he – and we – need a simple term summarizing the manifold ways that road traffic impacts natural systems. So he invented the word which serves as the title of his important new book Traffication: How Cars Destroy Nature and What We Can Do About It.

The field of study now known as road ecology got its start in 1925, when Lillian and Dayton Stoner decided to count and categorize the road kill they observed on an auto trip in the US Midwest. The science of road ecology has grown dramatically, especially in the last 30 years. Many road ecologists today recognize that road kill is not the only, and likely not even the most damaging, effect of the steady increase in traffication.

Noise pollution, air and water pollution, and light pollution from cars have now been documented to cause widespread health problems for amphibians, fish, mammals and birds. These effects of traffication spread out far beyond the actual roadways, though the size of “road effect zones” vary widely depending on the species being studied.

Donald is based in the United Kingdom, but he notes there are relatively few studies in road ecology in the UK; far more studies have been done in the US, Canada, and Western Europe. In summarizing this research Donald makes it clear that insights gained from road ecology should get much more attention from conservation biologists, transport planners, and those writing and responding to environmental impact assessments.

While in no way minimizing the impacts of other threats to biodiversity – agricultural intensification and climate change, to name two – the evidence for traffication as a major threat is just as extensive, Donald writes. He cites an apt metaphor coined by author Bryan Appleyard: the car is “the Anthropocene’s battering ram”.

Traffication has important implications for every country under the spell of the automobile – and particular relevance to a controversy in my own region of Ontario, Canada.

A slow but relentless increase

One reason traffication has been understudied, Donald speculates, is that it has crept up on us.

“These increases have been so gradual, a rise in traffic volume of 1 or 2 per cent each year, that most of us have barely noticed them, but the cumulative effect across a human lifetime has been profound.” … (All quotes in this article from the digital version of Traffication.)

“Since the launch of the first Space Shuttle and the introduction of the mobile phone in the early 1980s,” Donald adds, “the volume of traffic on our roads has more than doubled.”

Though on a national or global scale the increase in traffic has been gradual, in some localities traffication, with all its ill effects, can suddenly accelerate.

That will be the case if the government of Ontario follows through with its plan to rapidly urbanize a rural area on the eastern flank of the new Rouge National Urban Park (RNUP), which in turn is on the eastern flank of Toronto.

The area now slated for housing tracts was, until last November, protected by Greenbelt legislation as farmland, wetland and woodland. That suddenly changed when Premier Doug Ford announced the land is to be the site of 30,000 new houses in new car-dependent suburbs.1 And barring a miracle, the new housing tracts will be car-dependent since the land is distant from employment areas and services, distant from major public transit, and because the Provincial government places far more priority on building new highways than building new transit.

Though the government has made vague promises to protect woodlands and wetlands dotted between the housing tracts, these tiny “nature preserves” would be hemmed in on all sides by new, or newly busy, roads.

As I read through Donald’s catalog of the harms caused by traffication, I thought of the ecological damage that will be caused if traffic suddenly increases exponentially in this area that is home to dozens of threatened species. The same effects are already happening in countless heavily trafficated locales around the world.

“A shattered soundscape”

Donald summarizes the wide array of health problems documented in people who live with constant traffic noise. The effects on animals are no less wide-ranging:

“A huge amount of research, from both the field and the laboratory, has shown that animals exposed to vehicle noise suffer higher stress levels and weakened immune systems, leading to disrupted sleep patterns and a drop in cognitive performance.”

Among birds, he write, “even low levels of traffic noise results in a drop in the number of eggs laid and the health of the chicks that hatch.” As a result, “Birds raised in the presence of traffic noise are prematurely aged, and their future lifespans already curtailed, before they have even left the nest.”

Disruptions in the natural soundscape are particularly stress-inducing to prey species (and most species, even predators, are at risk of being someone else’s prey), since they have difficulty hearing the alarm signals sent out by members of their own and other species. To compensate, Donald writes, “animals living near roads become more vigilant, spending more of their time looking around for danger and consequently having less time to feed.”

A few species are tolerant of high noise levels, and seldom become road kill; their numbers tend to go up as a result of traffication. Many more species are bothered by the noise, even at a distance of several hundred meters from a busy road. That means their good habitat continues to shrink and and their numbers continue to drop. Donald writes that half of the area of the United Kingdom, and three-quarters of the area of England, is within 500 meters of a road, and therefore within the zone where noise pollution drives away or sickens many species.

Six-hundred thousand islands

When coming up to a roadway, Donald explains, some animals pay no attention at all, others pause and then dash across, while others seldom or never cross the road. As the road gets wider, or as the traffic gets faster and louder, more and more species become road avoiders.

While the road avoiders do not end up as roadkill, the road’s effect on the long-term prospects of their species is still negative.

When animals – be they insects, amphibians, mammals or birds – refuse to cross the roads that surround their territories, they are effectively marooned on islands. Taking account of major roads only, the land area of the globe is now divided into 600,000 such islands, Donald writes.

Populations confined to small islands gradually become less genetically diverse, which makes them less resilient to diseases, stresses and catastrophes. Local floods, fires, droughts, or heat waves might wipe out a species within such an island – and the population is not likely to be replenished from another island if the barriers (roadways) are too wide or too busy.

The onset of climate change adds another dimension to the harm:

“For a species to keep up as its climate bubble moves across the landscape , it needs to be able to spread into new areas as they become favourable . … In an era of rapid climate change, wildlife needs landscapes to be permeable, allowing each species to adapt to changing conditions in the optimal way. For many species, and particularly for road-avoiders, our dense network of tarmac [paved road] blockades will prove to be a significant problem.”

Escaping traffication

Is traffication a one-way road, destined to get steadily worse each year?

There are solutions, Donald writes, though they require significant changes from society. He makes clear that electrification of the auto fleet is not one of those solutions. It’s obvious that electric cars will not reduce the numbers of animals sacrificed as road kill. Less obvious, perhaps, is that electric cars will make little difference to the noise pollution, light pollution, and local air pollution resulting from traffication.

At speeds over about 20 mph (32 km/hr) most car noise comes from the sound of tires on pavement, so electric cars remain noisy at speed.

And due to concerted efforts to reduce the tailpipe emissions from gas-powered cars, most particulate emissions from cars are now due to tire wear and brake pad wear. Since electric cars are generally heavier, their non-tailpipe emissions tend to be worse than those from gas-powered cars.

One remedy that has been implemented with great success is the provision of wildlife bridges or tunnels across major roadways. In combination with fencing, such crossings have been found to reduce road kill by more than 80 per cent. The crossings are expensive, however, and do nothing to remedy the effects of noise, particulate pollution, and light pollution.

A partial but significant remedy can be achieved wherever there is a concerted program of auto speed reductions:

“Pretty much all the damage caused by road traffic – to the environment, to wildlife and to our health – increases exponentially with vehicle speed. The key word here is exponentially – a drop in speed of a mere 10 mph might halve some of the problems of traffication, such as road noise and particulate pollution.”

Beyond those remedies, though, the key is social reorganization that results in fewer people routinely driving cars, and then for shorter distances. Such changes will take time – but at least in some areas of global society, such changes are beginning.

Donald finds cause for cautious optimism, he says, in that “society is already drifting slowly towards de-traffication, blown by strengthening winds of concern over human health and climate change.”

There’s scant evidence of this trend in my part of Ontario right now,2 but Donald believes “We might at least be approaching the high water mark of motoring, what some writers refer to as ‘ peak car ’”. Let’s hope he’s right.

1 A scathing report by the Province’s Auditor General found that the zoning change will result in a multi-billion dollar boost to the balance sheets of large land speculators, who also happen to be friends of and donors to the Premier.

2 However, there has been a huge groundswell of protest against Premier Doug Ford’s plan to open up Greenbelt lands for car-dependent suburban sprawl, and it remains unclear if the plan will actually become reality. See Stop Sprawl Durham for more information.

Note to subscribers: the long gap between posts this summer has been due to retina surgery and ensuing complications. It’s too early to tell if I’ll be able to resume and maintain a regular posting schedule, but I do hope to complete a post on transforming car-dependent neighbourhoods as promised in May.

in and around the woods

PHOTO POST

The forest floor is still cold and in many places soggy. But the flowers that live there are in a hurry to bloom before the canopy fills in and blocks the sunlight.

That means there is a lot of beautiful change happening every day – and a lot of delicate growth that might be crushed by a hasty, careless or disrespectful step.

The first blooms of Trillium are just now emerging.

Leaf Over Leaf

Skunk Cabbage is a common Ontario woodland plant but I haven’t seen any within walking distance of home. The one photographed below is along the Seaton Hiking Trail in north Pickering. I saw scores of them popping out of the mud in particularly wet areas. Botanists use the word “spathe” for what most of us would call “that purple and gold pointy-curvy thing that sticks up beside the leaves.”

Let’s call a spathe a spathe

American Goldfinches are singing their songs throughout the neighbourhood, including from the branches of small trees at the edge of the woods.

Sunny As Spring

The tiny perfect flowers of Coltsfoot light up muddy creek banks.

Coltsfoot on Creekbank

Within the woods are many species of mosses. I found that by holding a reading magnifier in front of my camera lens I can get slightly improved pictures of the delicate features. The trick is to get down low enough on the ground so I can look up through the moss. The more detail I see, the more I think “I’d really like to get a more powerful lens.” (If I do get one, obviously, I’ll think “I should get an even more powerful lens.”)

Floor to Ceiling

Periscope

In the marsh next to the woods I was lucky enough to come across this female Common Merganser. (Not a fair name for such a splendid bird, I agree.)

Merganser Watch

This male Wood Duck may live nearby; Wood Ducks nest in trees although much of their diet comes from the marsh.

Marsh Moiré

Tree Swallows spend many hours swooping gracefully over the waters of the marsh while dining on insects. This pair was checking out a prefab house now available in the savannah just between the marsh and the woods. Location, location, location.

Sheltering Swallows 1

Sheltering Swallows 2

Sheltering Swallows 3

Skittering from tree to tree are the squirrels, keeping the forest lively throughout the seasons.

Upon Closer Inspection

For full-screen view of composite at top of page, click here.

 

The uncertain prospects for us multicell types

Also posted on Resilience.

You and I and termites have a lot in common. For one thing, we are all dependent on microbes to stay alive (though few microbes depend on us).

A Natural History of the Future, by Rob Dunn, Basic Books, November 2021

Besides, humans and termites, along with every other multi-celled living creature, belong to just one small branch on the evolutionary tree of life. All of us multi-celled types together – be we plants, insects, fish, birds or apes – are barely a rounding error in the catalogue of life, in which the overwhelming majority of varieties of life are bacterial.

These perspective-correcting points loom large in Rob Dunn’s A Natural History of the Future (Basic Books). If it were merely a compendium of curiosities the book would still make a really good read, given Dunn’s ability to highlight recent work by dozens of other researchers combined with his gift for clear exposition. But in his discussion of key laws of ecology Dunn has a practical purpose in mind: he wants to give us a better chance at surviving this new age of instability which we call the anthropocene.

In spite of all our clever technologies, he argues, human life is and always will be limited by basic principals of ecology. These laws of ecology are particularly important as we leave a millennia-long period of relative climate stability and begin to cope with the climate chaos we have created.

Climate change sometimes recedes into the background in A Natural History of the Future … for a few pages. Dunn takes us billions of years back into evolutionary history, and he spends much of the book reviewing events of recent decades, but his aim is to elucidate our near future. And in the near future no challenges loom quite so large as climate change.

In the big picture, think small

At the outset Dunn helps us understand the scope of our ignorance. When Western scientists such as Linnæus started to classify species, they focused mostly on species which were relatively large, beautiful, or directly useful to us. These scientists also tended to work in northern Europe, an area with very little biological diversity relative to much of the world.

By the second half of the twentieth century this limited world view was being challenged from within academic science. Once they paid close attention, ecologists realized that species of insects vastly outnumber all the species of larger animals. As Terry Erwin wrote in 1982, “there might be 30 million tropical arthropod species.”

Other scientists were exploring the bewildering variety of fungi. Still others, aided by new techniques in genetics, got a glimpse of the staggering diversity of bacteria. A study published in the National Academy of Sciences in 2016 “estimated that there might be a trillion kinds of bacteria on Earth.”

Dunn summarizes the perspective shift in these words:

“By the time I was a graduate student, Erwin’s estimate had led scientists to imagine that most species were insects. For a while, it seemed as though fungi might be the big story. Now it seems as though, to a first approximation, every species on Earth is a bacterial species.” (A Natural History of the Future, page 28)

‘A Novel Representation of the Tree of Life’ (from Nature, 11 April 2016), shows the predominance of bacteria in the tree of life. Dunn includes a simplified version of the same graphic, and he writes: “All species with cells with nuclei are part of the Eukaryotes, represented in the lower right-hand section of the tree. … The Opisthokonta, one small part of the Eukaryote branch, is the branch that includes animals and fungi. Animals, if we zero in, are just one slender branch of the Opisthokonta. … [V]ertebrates do not get a special branch on the tree. The vertebrates are a small bud. The mammals are a cell in that bud. Humanity is, to continue the metaphor, something less than a cell.” (Graphic by Laura A. Hug, Brett J. Baker, Karthik Anantharaman, Christopher T. Brown, Alexander J. Probst, Cindy J. Castelle, Cristina N. Butterfield, Alex W. Hernsdorf, Yuki Amano, Kotaro Ise, Yohey Suzuki, Natasha Dudek, David A. Relman, Kari M. Finstad, Ronald Amundson, Brian C. Thomas and Jillian F. Banfield; via Wikimedia Commons.)

For good or ill, our smaller companions on earth have always played large roles in natural history. Termites, for example, were just another type of cockroach until they acquired the gut microbes that allow them to digest wood. We humans “are probably dependent on more species than any other species ever to exist” – including, to mention just a few, all the insects that pollinate all the plants we eat, and all the gut microbes that help us to digest that food.

While we can’t hope to fully understand or even name all the varieties of life, we can, Dunn says, understand basic rules that influence how new species evolve, how existing species go extinct, and how species interact with each other and with their changing ecosystems. If we respect those rules we lessen the chances that we will threaten our own chances of survival any further.

Islands and corridors

The book covers too many subjects to adequately summarize in one review, but consider two simple concepts. A discussion of island ecosystems highlights the principle that bigger islands tend to have more species. It is equally true that ecosystems with greater diversity of species are more stable through time.

“Islands” can refer to bodies of land surrounding by water – but also to isolated specific habitats surrounded by very different ecosystems. One effect of our own rapidly climbing population and the explosive growth of urban habitats, Dunn explains, is the fragmentation of many ecosystem into an array of tiny islands – small areas of forest or plots of prairie – surrounded by cities or monoculture farms. These fragments – islands – are often too small to support a diverse number of species, and too widely separated from similar fragments for species to move between the islands. The result is that these islands are all highly vulnerable to significant or rapid change – including the change we are now enforcing by our rapid release of greenhouse gases.

The ecology of corridors is attracting wide interest, because it is readily evident that many species will need to move to survive. In some places and for some species, corridors that we carefully preserve or recreate may help plants and animals move along with the warming climate.

Corridor biology can also have unintended and unwanted consequences, Dunn points out. Not only are we building megacities, but these megacities are sometimes merging. In the nearly unbroken urban area from Washington DC to New York City,

“We have already created a corridor, a perfect and immense corridor, but it is not a corridor for rare butterflies, jaguars, and plants. It is, instead, a corridor for urban species, species able to move along roads and live amid buildings, species that live not in green spaces but in gray ones.” (page 72)

A corridor, in other words, for pigeons, Norway rats, and less-beloved species including some of the parasites that plague people in warmer cities, and which will move north with ease as the climate heats up.

Diversity and stability

The global market economy has pumped hundreds of billions of tonnes of carbon dioxide into the atmosphere, and it has appropriated most of the world’s arable land for monocultures of a small number of staple crops. Taken singly each of these transformations would have destructive effects – but in tandem they put us in a real heap of trouble:

“We have built a food system that thrives when variability is minimized. But … we have also altered Earth’s climate in such a way as to make it much more variable and unpredictable.” (page 150)

The diversity-stability law implies that “Regions with a greater diversity of crops have the potential to have more stable crop yield from year to year and hence less risk of crop shortages” (page 11). Dunn cites analysis by Delphine Renard, who compared nationwide yields from 91 countries, for 176 crop species, over a 50-year period. The yields were summed in terms of calories, so that agricultural yields from corn to potatoes to peaches could be compared in a common unit of measurement. The result: Countries with high crop diversity experienced 25 percent overall yield declines an average of once in 125 years. Countries with the lowest crop diversity experienced 25 percent declines an average of once in eight years.

The coming century will be more challenging than the past century, Dunn says. It would be easier, though still difficult, if we could expect steadily rising temperatures in every area. That is not, of course, how climate change is working. Instead, the general heating trend will be punctuated at unpredictable intervals by damaging cold spells. Dry areas are likely to get dryer, but with occasional damaging downpours, while wet areas get wetter but experience occasional droughts.

Considering climate physics and ecological principles together, then, it is essential that we begin the re-diversification of agriculture.

Other topics that Dunn covers include the dangers in indiscriminate use of biocidal chemicals – be they antibacterial hand creams routinely applied, antibiotics routinely added to animal feed, or herbicides sprayed on nearly every major crop field in whole countries. He discusses why some types of avian intelligence will help birds cope with climate change, while other kinds of birds will be at a terrible disadvantage. He explains that in spite of our advanced technologies, the dense concentrations of humans occupy the same geographic areas today that we tended to favor 6,000 years ago; this is a subject I hope to return to in a coming blog post.

The final chapter focuses once again on bacteria. We humans will die off some day, Dunn says, because no species last forever. If we mess up in spectacular fashion, millions of other multi-celled species will go extinct along with us – mammals, birds, fish, insects, trees and flowers. But uncounted millions of unicellular species – teeming masses of bacteria that thrive in scalding heat, concentrated acids, or intense radiation – will survive any calamities we are able to bring on.

A Natural History of the Future is a big book in its scope and in the degree of detail. Throughout, Dunn makes things clear for non-specialist readers. Highly recommended.

Photo at top of page: A Mastotermes darwiniensis worker termite. The giant northern termite is a large endemic species which lives in colonies in trees and logs in the tropical areas of Australia. Photo courtesy of Commonwealth Scientific and Industrial Research Organisation (CSIRO), via Wikimedia Commons.