Trees, 2014

As I did last year, I’d like to catalog what trees I managed to plant this year (the ones marked as 0 replaced trees that died or had to be removed):

  1. Mammoth Pineapple Guava (replaces diseased Lemon)
  2. Fuerte Avocado (replaces mutant Lemon)
  3. Parfianka Pomegranate (replaces dead Queen Avocado)
  4. Parfianka Pomegranate (replaces dead Grapefruit)
  5. Ambrosia Pomegranate
  6. Fuyu Persimmon
  7. Meyer Lemon
  8. Eversweet Pomegranate
  9. Reed Avocado
  10. Washington Navel Orange
  11. Valencia Orange
  12. Manila Mango
  13. Mysore Banana
  14. Parfianka Pomegranate
  15. Hass Avocado
  16. Eversweet Pomegranate
  17. Coolidge Pineapple Guava
  18. Manila Mango
  19. Capulin Cherry
  20. Sir Prize Avocado
  21. Dwarf Cara Cara Navel Orange
  22. Mexican Cream Guava
  23. Kona Sharwil Avocado
  24. Ettinger Avocado
  25. Unique Pineapple Guava
  26. Nazemetz Pineapple Guava
  27. Cripps Pink Apple
  28. Bacon Avocado
  29. Gwen Avocado
  30. Hass Avocado
  31. Kona Shawil Avocado
  32. Pinkerton Avocado
  33. Reed Avocado
  34. Ice Cream Banana
  35. Janice Kadota Fig
  36. Lemon Guava
  37. Lemon Guava
  38. Lemon Guava
  39. Lemon Guava
  40. Strawberry Guava
  41. Manila Mango
  42. Fuyu Persimmon
  43. Nazemetz Pineapple Guava
  44. Seedling Pineapple Guava
  45. Seedling Pineapple Guava
  46. Unique Pineapple Guava
  47. Unique Pineapple Guava
  48. Parfianka Pomegranate
  49. Eversweet Pomegranate
  50. Chestnut White Sapote
  51. Santa Cruz White Sapote
  52. Walton White Sapote
  53. Reed Avocado

Efficiency as a Vice

In modern economic thought, efficiency is paramount. The goal of economic systems, and entities within those systems, is to maximize efficiency. Policymakers are supposed to remove impediments that are making markets inefficient, and cut government inefficiency.

Even those that claim not to buy into such thinking often still do without realizing it. There have been many hundreds if not thousands of papers and articles by critics of mainstream economic thought on how the “efficient market hypothesis” is wrong, and that markets today aren’t efficient or are broken in other significant ways despite their efficiency (e.g. “markets may be efficient but don’t consider human happiness”). However these critics are still buying into the framing of efficiency as king (and thus as the thing to inveigh against). Ultimately these arguments are saying that “if only we were to make change X to the system, then it will be properly efficient.”

A key aspect of photosynthesis is thought to have evolved only once. But that one time was enough, and was such an evolutionary advantage that we’ve had it and relied upon it ever since. However, it’s far from efficient — most plants only use a couple percent of the energy they receive from the sun.

Consider a highly-efficient solar panel farm — panels at just the right angles, tracking the sun, covering every inch of ground. From one perspective this is the pinnacle of technological development: shiny, “green” technology, silent and efficient (much more so than a plant’s leaf). But in ecological terms the landscape is a wasteland: no light is allowed to reach the ground for any other use, and as a result it’s likely next to nothing else will live there. (And we’re already seeing the impact of this — desert ecosystems are hurt where solar arrays are being built, and sometimes the carbon lost from the desert soils as a result is greater than the fossil-fuel carbon offset by the solar electricity production.) The landscape is efficient in a narrow sense, but it’s not clear that that’s what we should want.

Compare that to a forest’s use of sunlight, in which layer upon layer of foliage, from the canopy to the forest floor, take part in a dance of extracting what little they can from the sun’s rays, and sharing that with a huge diversity of species. Those species are arranged in a complex web of interactions such that no species is truly on top of a hierarchy — every species is in the middle of some part of the food web, and the density of connections between them ensures that the forest ecosystem can continue to function as these links disappear and new ones are created.

Consider the structure of network routing on the Internet. (Background: the Internet is decomposed into what are called ASes — Autonomous Systems — each of which is a large organization such as a company or university. Using the routing protocol BGP, ASes announce routes to IP addresses on the Internet to one another, and store the announcements they hear from others. When data packets arrive at an AS, it uses its knowledge of currently available routes to the packets’ destinations to forward them to the next AS along the path to the destination.) While the Internet is thought to be resilient — the apocryphal story is that it was designed to survive nuclear attack — the connectivity of the Internet is not nearly as resilient as is assumed. Specifically, there are roughly a dozen large ASes (the large telecom companies that provide most long-distance connectivity) that the Internet depends upon for its operation. Most paths between two destinations go up to a large AS and then back down to the final destination.

The networking specialist reading this might say, well wait a second — those individual autonomous systems are internally resilient, as they are composed of a large data plane of many thousands of routers. That’s true, and that does provide a degree of resilience — it’s why we don’t see huge outages on a regular basis. But they rely upon a single protocol for the control plane, and a handful of system administrators and programmers to keep that control plane in check. (The network’s data plane consists of the paths through wires and networking devices like routers and switches over which data — packets — flow for delivering useful service. The network’s control plane consists of the systems used to manage the network’s data plane; the control plane may be distinct from the data plane, or it may rely upon the data plane for its own communication.) Regional-scale disasters have had huge ripple effects in Internet connectivity — the Baltimore tunnel fire of 2001, the Taiwan earthquake of 2006 — while simple misconfiguration in a single spot has caused the entire Internet to go down. In each instance, network engineers put in place fixes to deal with the proximate cause of the outage, but the broader issues of a hierarchical, efficient, and un-resilient Internet remain. For the Internet to be truly resilient, in the way nature is, it would likely have to have less hierarchical routing, more backup network links, more diversity in ASes, and as a result would not be as profitable for the large corporations that carry much of the Internet’s traffic.

As a final example, a couple of years ago I looked at the challenge of using nuclear energy in hard times. Operators of such plants frequently ask and receive the go ahead for power uprates — they rely on the fact that each plant was built with some amount of safety margin, and cut into that safety margin so as to operate at a higher power yielding greater profit. (In re-reading my post on nuclear, I’m sad to say that large-scale solar thermal — which I was hopeful about — is looking more problematic than I thought then. Still, small-scale solar thermal works great and is even simpler.) Once again, the temptation to reach for efficiency, which is currently the primary virtue for any organization, trumps other concerns.

It seems to me that we need to openly begin questioning the dogma of efficiency as the main aim for all systems — economic, technological, social — a dogma that permeates modern life in many spheres — political, corporate, academic — even when it isn’t acted upon in every case. Instead, perhaps we can aim for inherent complexity in our systems, just like nature, ensuring resilience over efficiency.

The Societal Cost of Computer Science

(I’ve been sitting on this post about abstraction, indirection, and disintermediation for nearly a year, figuring I’d flesh out the argument into a long post with numerous examples; Greer’s post tonight is on a similar topic, so I decided I might as well post it as is.)

It’s often said as a joke among computer scientists (especially among those who work on systems, as opposed to theory) that there are really only two ideas in the field: abstraction and indirection. I’d like to explain what happens when these ideas (more about which in a moment) are applied not just in the abstruse confines of software and hardware and computer systems but instead are applied to a society as a whole. While it might seem like a leap to say that such academic principles of computer science impact society, I’d like to make that case that that’s exactly what’s happened while we weren’t looking.

Computer science is an odd field — it consists of everything from pure mathematics (e.g. computational complexity theory), applied mathematics (e.g. algorithms and cryptography), engineering (e.g. distributed systems), and even some of what we might traditionally call science (e.g. Internet measurement). Computer scientists might bristle at the following, but to a first approximation subfields within computer science fall broadly into two categories: theory and systems. My academic background is in the latter, though I’m also fairly familiar with theory as well. Theory includes algorithms and complexity theory.

There’s been a movement of sorts for the last decade to attempt to quantify everything, as technologists expand their vision and reach and dominance in society. From crime fighting to education to governance to personal health to many many more fields, computer scientists have jumped in with both feet, and more than that, people have welcomed their dominance, perhaps from a perspective that “data will set us free.”

The DIKW — Data, Information, Knowledge, Wisdom hierarchy — is a nice classification, and one that I think more computer scientists should consider. To put it simply, I think we’ve seen a replacement of a smaller amount of knowledge and wisdom for a larger amount of data and information, in the hopes or claims that more is better. We have shoes that will tell us how fast and how far we’ve run, phones that can and do monitor everything from what we’re currently doing to what someone else is typing nearby, purportedly crime-fighting cameras and microphones, and much much more. But it’s not clear that any of this is turning into knowledge or wisdom — my hypothesis is that knowledge and wisdom have a fundamental limit, in that they are generated by slow processes of human minds and human interactions, and more data or information won’t help speed that up.

But I think the impact of computing on society goes deeper, and its root is the two concepts of abstraction and indirection.

Abstraction in computer science terms, roughly speaking, is the process by which some computational object — anything you can represent in terms of some data stored in a computer — is boiled down to a set of data fields that describe it. Think of any concept stored by a website you use, and there’s lot of abstraction going on, a lot of it visible from the outside if you know what to look for. For example, many companies publish APIs (Application Programming Interfaces), which are the means by which you can integrate with their software / systems. Those APIs come with descriptions of the abstractions they use to convey information. Want to see what your friends look like to Twitter? Just look at their API — your friends are just a list of numbers. The benefit of abstraction in computing is that it enables code to be written generically and modularly — a friend in code is a simple abstract concept that can be described with a few data fields, rather than a real complex human relationship around which code must be adapted.

Indirection in computer science terms is the process of interposing on some communication — the process of decoupling two things that were coupled and sticking a layer in between. The benefit of indirection is that it can enable flexibility. For example, Amazon to a large extent relies upon indirection — many of the warehouses they operate are not actually run by them, but by warehouse contractors under their direction, and the products they sell aren’t made by them, nor are the reviews written by them. The benefit, so far as there is one, is that by creating many layers of indirection in between, they enable their users to learn about and purchase just about any products manufactured anywhere in the world and stored at some large warehouse out there.

There’s obviously a dark side to both abstraction and indirection, and it’s been written about a lot, but I think it hasn’t been recognized as such. That is, the systems that employ abstraction bother us at a gut level — the fact that Facebook has cheapened friendships, that Amazon commodifies all products and all sellers — but it’s not often recognized that at its root it’s just abstraction gone awry. The same goes for indirection. Cloud computing is a good example of the use of the two systems ideas together — your data is held in some abstract conception of a data storage system — the cloud — and you don’t even communicate with the cloud servers directly but rather through a labyrinth of intermediate systems and layers all with a friendly face on them. Virtually every website, Internet service, and tech startup leverages abstraction and indirection; they abstract the previous provider of the service and become the layer through which the two sides interface — take Uber, which abstracts away the Taxi driver and inserts itself as the middleman in the transaction and takes a hefty cut. (Note, however, that traditional software doesn’t do this — an old fashioned calculator program, for example, is abstracting and indirecting much less.)

Those that don’t insert themselves as the middleman in a previous paying relationship create a new one via advertising (and apply indirection there). It’s been said by Bruce Schneier that the business model of the Internet is surveillance. That is, many companies make money on the Internet by collecting data on people so that they can sell better advertising. I think this is true, and again I think the fundamental issue here, the cause of the structure of business on the Internet, is these two key ideas of computer science. Understanding those ideas might be important in a range of challenges we face as a society — both the obviously related ones like surveillance and less obviously related environmental and socio-economic challenges.

Am I saying as a computer scientist that we should abandon the field? No. But perhaps there are a few things we — both computer scientists and the broader public — need to discuss:

a) that data and information are just representations of the real world, and our current society tends to favor these representations over the messiness of reality,
a’) and we need to resist this.

b) that intermediation on things in the abstract world can intermediate things in the real world,
b’) but it’s possible to apply this idea in reverse and disintermediate and
b”) it’s possible to identify and remove computers in natural systems and human society and remove them if the only reason the computers are still present is legacy.

Should we perhaps move towards building computing tools rather than computing systems?

No True Permaculture

I do a fair bit of gardening in public or semi-public spaces — sidewalk strips, parking lots, yards of large buildings, rooftops — and over the last couple of years I’ve had a lot of conversations with people passing by about gardening, fruit trees, sustainability, and lots more. One topic that has come up infrequently but consistently with those with a serious interest in gardening is permaculture. Sometimes it’s just a discussion about permaculture, sometimes it’s about the person having done or planning to do a permaculture design course (PDC), sometimes it’s about various techniques that are associated with permaculture (e.g., herb spirals, swales, perennial polyculture, etc.).

But more than all that, I’ve been asked a question a few times that I’m never able to answer: “Do you do permaculture?” I usually go quiet for a moment, think about it, and eventually give a few caveats but answer “No, I don’t do permaculture.” There are a few reasons I answer that way — I’ve never taken a PDC, I don’t specifically try to do permaculture but pick and choose from whatever I find promising, etc. — but none of these are related to my main reason: I don’t know what is and isn’t permaculture. (Sometimes I think this is because I don’t have a lot of years of active gardening under my belt, but sometimes I think it’s deeper, and it’s the latter notion I want to explore.)

I look at what I do in some garden settings, where true sustainability isn’t possible (i.e., a garden that would continue growing for many years without human intervention — rooftops especially), and I wonder how that could ever be called permaculture. But then I see discussion of permaculture roof gardens and the like and get confused. I imagine that if one were to analyze many of these types of unconventional gardens according to the principles of permaculture, they wouldn’t hold up well. When I read about gardens / farms in which people try to get high yields using permaculture-associated techniques, and then see rebuttals that those projects weren’t really permaculture, I’m left to wonder whether the No True Scotsman fallacy applies to permaculture. That is, any project or site that is unsuccessful or undesirable from the perspective of the reviewer can be deemed to not be “true permaculture”. This excellent post gets at a number of concerns and confusions I’ve had, and points out the claim made by some permaculturists that failed or failing projects aren’t permaculture — again, the No True Scotsman fallacy.

I should step back and say that I’ve learned a lot from reading some permaculture gardening books (especially Gaia’s Garden), but that these days I find I’m learning the most by reading and participating in rare fruit growing forums/groups, and have had the most success from simple trial and error. Despite all this, I hope that there is a next wave to come — in the form of new ideas, techniques, principles, or something else entirely — that advances everyone’s thinking about sustainable horticulture beyond the plateau we’ve reached today, whether it’s permaculture or not.

The Energetic Basis of Wealth

Last year I did an analysis to try to understand whether it’s possible to feed the world sustainably. Today I’d like to try to understand what happens to countries as they must rely upon the sun for energy (and, indirectly, wealth).

An old proposition in the sustainability community is that the material wealth we enjoy today in industrialized nations is based in large part on our energy consumption. Take that away, and our vaunted industrial, intellectual, and entrepreneurial prowess will do little to sustain our material wealth. I think there’s quite a bit of truth in this claim, and the data at least supports the notion that there is a correlation — Gapminder enables charting of fairly-recent energy and economic data; this chart shows energy use per capita vs. GDP per capita. (One thing you can see, if you move the year slider at the bottom of the chart, is that while individual countries have moved up or down over the years, the correlation has remained remarkably constant.) In any case, for the purpose of this post, I’m going to set the validity of the claim aside and assume that it’s true. I’m also going to set aside the problem with using GDP to measure wealth, as it doesn’t really matter for the analysis below.

So, supposing that wealth (per capita) as we currently conceive of it is based in the flow of energy (per capita), where does that leave us in a world with few or no fossil fuels? Well, we could look to alternative energy sources, but I’m going to take Odum’s assertion as a given: “The natural conversion of sunlight to electric charge that occurs in all green-plant photosynthesis after 1 billion years of natural selection may already be the highest net emergy possible.” This means that we can assume in pure net emergy terms that growing plants to fuel society directly and indirectly is more efficient than most alternative energy schemes. (I’ll come back to the case of Iceland later.)

That brings us back to what the land can yield. In my calculations last year, I estimated that arable land yields about 1-2 W/m^2 of harvestable energy. Given that, we can then estimate the potential energy (really power, since it’s in terms of Watts) yield per country by looking at the arable land available per capita. This dataset from the World Bank provides hectares per person for the countries of the world.

At the top of the list is Australia, which, if climate change doesn’t hit its arable land hard, will have a huge 2.13 hectares per person to work with. Multiplying the land energy yield of 1-2 W/m^2 and we get 21.3 kW to 42.6 kW per person — a huge potential value. The United States, at 0.51 hectares per person, would be at 5.1 kW to 10.2 kW per person; today the U.S. uses about 10 kW per person, so this isn’t far off. China is at 0.13 hectares per person, which would be 1.3 kW to 2.6 kW per person — also not far off from today. The countries that are most obviously in trouble, by this calculation, are those that have extraordinarily high energy use today but little arable land — many nations in the Middle East and small, wealthy nations like Luxembourg and Singapore fall into this category. Earlier I said Iceland is a special case; it has high energy use but may be able to sustain it because of its unique geothermal resources.

Granted, this calculation assumes intensive cultivation and doesn’t account for the need to feed the people (and animals) that do the work, and there’s a diminishing return on hectares per person (that is, it’s unlikely that a single person will be able to double their personal energy yield going from 1 hectare to 2 hectares, since it’s just too large for one person to intensively cultivate at that point). I think it’d be fair to halve the values, at a minimum, to account for this. And due to the need for a large fraction of the population to be involved in growing plants at least part time, there’d necessarily be less time for other work, and that would likely shrink the range of specialized occupations from what we have today. Despite all this, the calculation still indicates that a country like Australia could be in good shape — not far from where it is today — if it were to really transform itself economically so as to base its wealth on sustainable horticultural practice. That is, it might be able to achieve a fairly high equilibrium state of both energy use per capita and wealth per capita. And even the United States wouldn’t be that far off — perhaps 50-60% lower than today.

What does this mean for the future? I’m not sure, but I think it indicates that when the fossil fuel trapdoor opens there’s potentially a floor not far beneath our feet, one that’s available to us if we’re willing to do the hard work to base society’s wealth on what the sun provides to us through plants.

Growing Degree Days

Most gardeners are familiar with the idea of hardiness zones — the USDA hardiness zone map, for example, breaks down regions of the U.S. by their expected minimum winter temperature. The idea is that, for example, in Zone 10a (which I’m in), which is listed as 30-35F minimum temperature, the expected low each winter will not be below 30F. Most plants sold are described in terms of their hardiness zone — a plant that is listed as say USDA hardiness Zone 8b should survive in Zones 8b and above. Zone 10a is almost the warmest you can get in the continental U.S. — there are only parts of Southern California and Southern Florida that are in higher zones. And so you would think by virtue of being in 10a that where I live it’d be possible to grow just about anything.

But common sense says that something is missing in this analysis, as does the fact that there are plenty of plants and trees that survive but don’t thrive here. The climate here is the usual Pacific marine climate that predominates along the California coast — a fair amount of fog and wind, moderate rainfall and essentially no frost in winter, and not a lot of warmth. Even in the peak month of summer — which is September here, delayed by the ocean’s thermal inertia — the average high temperatures barely make it into the low 70s F. By the hardiness zone concept, one might expect it to be a great place to grow things, but it’s only okay. I’ve often wondered what concept might explain why gardens in hotter, more inland areas nearby tend to flourish while those here struggle.

I think the concept I’ve been looking for is Growing Degree Days (GDD), which provides the key missing information. GDD is a strange concept, with a stranger unit of measurement. Instead of measuring temperature, or time, it’s in units of temperature multiplied by time. GDD is often based on 50F or 10C, as follows: take the average temperature of the day, A, by averaging the day’s high and low, and subtract from it the baseline B (usually 50F or 10C): X = A – B. X is the number of degree-days you accumulate for that day. Do the same for each day in the year (or growing season, for annuals) and sum it up (ignoring days that have negative values), and you get a measure of how much growing heat was accumulated by plants. 50F is used as a standard baseline, under the assumption that 50F is the minimum temperature for many plants to grow. Below that temperature they are effectively dormant.

You can easily find your local GDD information using this Growing Degree Days calculator. I put in local info and it was a revelation — it explained to me why tomatoes, peppers, squash, and many other annuals struggle to mature here before autumn weather kicks in — they just don’t get the accumulated warm growing time they need. And I saw that nearby inland locations have a 50% higher GDD50 than along the coast.

For fruits that need more heat to mature and sweeten — say Oranges or Pomegranates — you can select 60F or even 70F as a baseline. There again, I found that we just don’t have the heat along the coast here to grow sweet Oranges — something many gardeners in this area could attest to. Not all fruit trees require high GDD to produce mature, good tasting fruit. And indeed some fruits actually need lower values to produce well — some grapes for instance don’t like too much heat while other cultivars require it. Avocados, as it happens, don’t seem to need much heat to produce good fruit, but they can’t stand too much cold in the winter. Some fruits — like bananas — seem to need a combination of heat and no frost, and so they’re among the hardest to grow outside of the tropics.

So this post isn’t to say that the hardiness zone concept isn’t useful — GDD doesn’t tell you what will survive the winter. But both concepts are needed to determine a) what will survive the winter (hardiness) and b) what will grow well (GDD).

Growing Avocados

There isn’t much widespread knowledge about growing Avocado trees, especially outside of the few regions they’re grown commercially. I’ve been pretty singularly focused on growing Avocados in the last few years, but in sub-optimal climates, and wanted to share some of the hard-to-find information I’ve come across. (Disclaimer: I don’t claim any special knowledge beyond a serious interest in the subject and I don’t want to duplicate much of what’s already written in the Avocado wikipedia entry among other sources.)

There are a number of reasons I think Avocados are worth growing: they’re one of the few sources of plant-based fats (and non-starch calories), they have a broad spectrum of nutrients, they can be harvested over a long period and don’t drop off the tree that easily, they’re relatively pest free, and, of course, they’re delicious. Also, a new and somewhat sad reason has come up: Citrus greening disease, which is wiping out Citrus trees worldwide. Avocados can grow well in most places that Citrus grow today; Citrus that succumb to greening could be replaced by Avocados.

So suppose you want to want to grow Avocados. Well first let’s examine the optimal climate, and then see how far we might be able to stretch it. Some of the best climates for growing Avocados in the United States have December average daily low temperatures in the mid-high 40s F (8 C) and average daily high temperatures in the mid 60s F (18 C), and August average daily highs in the high 70s F (25 C). (Since they get little rainfall in Southern California, Avocado orchards are of course irrigated at great expense.)

My interest has been growing Avocados outside of that optimal climate. So there are a few things to know. First, the three types have different properties both in fruit and in growing conditions. Second, it’s possible to give them what they need outside of their optimal climates.

There are broadly speaking three types of Avocado: Mexican, Guatemalan, and West Indian (there are of course numerous crosses between them). Avocado trees, like many other fruit trees, don’t grow true to type if grown from a seed — start an Avocado from seed and you never know what you’ll get (and it’s generally thought to be unlikely you’ll get a tree that produces tasty fruit or any fruit at all, though you will most certainly get a beautiful tree). If you have land to spare and live in a marginal climate, I would recommend starting many Avocado trees from seed to find what survives in your region, but this approach can take many years of patience. So most Avocados come from grafted trees of a specific cultivar. Hass, the most common cultivar grown today, was discovered in Southern California in the early 1900s, and is thought to be mostly Guatemalan with a bit of Mexican genetics. But there are many, many more cultivars, some of which I’ll talk about below.

West Indian Avocados grow well in the Caribbean, Florida, and similar areas that have hot, humid, and wet climates. However the large light green-skinned fruit they produce aren’t generally as flavorful as the Guatemalan / Mexican varieties I’ve come to love — West Indian Avocados are low in oil content and more watery. I have to admit that I don’t have much to say in their favor, and will focus on the other two types.

Guatemalan Avocados are most similar to the rich, nutty, creamy varieties available at the store — Hass and its relatives. Guatemalan cultivars are the most sensitive to frost, and when young can barely handle any time below freezing without protection, but as mature trees can handle a few degrees below freezing before succumbing. They do best in regions with a smaller temperature range, such as along the coast. Other Guatemalan or mostly-Guatemalan cultivars include Reed, Gwen, Queen, Kona Sharwil, and Pinkerton.

Mexican Avocados are also quite tasty though not quite as rich in flavor as Guatemalan varieties — Mexicola Grande is one of the better known cultivars — and are able to thrive in locations with more winter frost and more summer heat. They have been known to survive temperatures of 20 F (-7 C) (some claim even lower). Their fruit is generally smaller than the other two types, and has very thin skin (that is often deep purple-black). Other Mexican cultivars include Mexicola (non-Grande), Bacon, and Zutano.

Mexican-Guatemalan hybrids thrive in in-between climates — regions with some coastal influence but more heat in the summer and cold in the winter. Fuerte is one among many such half and half cultivars, and Ettinger is another such hybrid.

In their optimal climates, Avocados are split into type A and type B, which indicate their flowering pattern. It’s thought that you’ll need a type A and a type B for cross-pollination to get fruit. However outside of regions that are as warm and temperate as Southern California, the trees get confused about their flowering schedule and having the two types is less important. In general, though, Avocado trees produce better when they have cross-pollinators.

The trees don’t appear to be too picky about soil, but they don’t like waterlogged soil (which can cause root rot) and have shallow feeder roots so do best with a thick layer of coarse, weed-free mulch underneath (e.g. leaves, tree trimmings, wood chips, etc.). Planting them a little above natural grade can help avoid waterlogging and keep them slightly warmer. A deep watering once per week when there isn’t rain seems to be sufficient, though there are plenty of mature Avocado trees I’ve seen that are growing and fruiting in Northern California without any care at all, surviving year-round just on the rain they get during rainy winters. While they will grow in containers, it’s unlikely they will fruit. Generally they need full or near-full sun to do well, though cloudiness doesn’t seem be an issue as they grow in plenty of cloudy / foggy coastal locations in California.

Most Avocados are grown in tropical, subtropical, and Mediterranean climates, but I suspect that it’s possible to grow Avocados much further North than they are currently grown. And beyond that, as climate zones slowly shift pole-ward, places that an Avocado might just barely survive now might be able to get fruit in a few decades.

As it stands, I know that it’s possible to grow Avocados in most parts California, much further North than most people are aware — virtually to the Oregon border. Within the U.S. I’d bet that Mexican cultivars (or hybrids that are mostly Mexican and part Guatemalan) could grow in a number of spots along the Oregon and Washington coast (and/or on hillsides of near-coastal sheltered valleys — assuming the hillsides get less frost than the valley floor, which is usually the case). Outside of the U.S. it might be possible to grow them in regions like Southern England, along the West Coast of France, and maybe even protected coastal areas of Belgium and the Netherlands; also much of coastal Japan could likely grow Avocados. Elsewhere they can be grown in large greenhouses, but you’d need to ensure a moderate temperature range and that (for Mexican and Guatemalan varieties) the humidity doesn’t get too high. When living outside of the right climate it can be hard to get grafted trees of specific cultivars; however I’ve found that local fruit tree nurseries will often do a special order if you ask.

When grown outside of their optimal climate, Avocado trees will sometimes lose their leaves when young or when stressed by cold or over-watering. Sometimes the leaves will just turn brown and hang on the tree for months through the winter, only to drop in the spring when new leaves come in. So don’t assume the tree is dead just because it’s lost its leaves in the winter.

Beyond selecting the right cultivars, it’s also fairly easy to create a microclimate that is a few degrees warmer than the surroundings by adding more temperature buffers (e.g. rocks, water features, concrete, etc.), cold air drainage (e.g. downslopes from the Avocado so cold air can flow away on cold nights), and placement so that the tree gets sun as early as possible on winter mornings. Growing against a South-facing wall (in the Northern Hemisphere) can help. With these steps, plus protection while the tree is young, and I think Avocados could be grown far and wide.

Rube Goldberg Nature

The more I learn about it, the more Nature looks like a Rube Goldberg machine: energy and materials flow through convoluted paths to accomplish something seemingly simple. Take the process by which a leaf decomposes. The sheer number of biogeochemical processes involved in the use of that leaf during decomposition is amazing: consumption by fungi and bacteria, use as shelter / habitat by soil nematodes and other microscopic organisms, consumption at a macro scale by larger soil organisms like earthworms, beetles, and crustaceans, use by natural geochemical processes in soil formation or water storage, and far more that I don’t know about (and that I’m sure even researchers in the field are still discovering).

A wild ecosystem involves countless intricate relationships, some essential to the functioning of the broader ecosystem (e.g. those between keystone species and others). Many of the relationships in such ecosystems produce yields of energy (and thus life) for creatures that have no immediate use to humans, and may even be pests on some level.

In many of our human systems, however, in the name of efficiency we engineer out the middle steps. Obvious examples of this abound in the industrial food system. An industrial CAFO is a bastion of efficiency, of a narrow sort. Food arrives (from the outside, typically) in a highly energy-dense and processed form, ready for conversion by the machine-animals from carbohydrates into meat and other products. Any waste products that can be used by humans are siphoned off during this process for sale; any that can’t be used are sent to waste lagoons and the like. The process is linear and of low complexity — food comes in one end, meat and waste on the other.

Consider how it’s often found that eating a fruit delivers vitamins more efficiently than taking a multivitamin. What in the mimicry of the natural vitamins is the multivitamin tablet missing? Instead of opting for the complexity of the fruit, we get orange tablets that can be churned out much faster and cheaper than growing oranges.

The problems inherent in such a way of thinking about and working with Nature is well known. What’s a better way of approaching it? It’s often been argued that the solution is to mimic nature. (This is indeed the approach taken by several agroecology systems, like permaculture.)

But there’s something missing here — and maybe the problem is inherent to some (but hopefully not all) attempts at biomimicry. Suppose I were to build a computer system that tries to learn from Nature. We spend some time analyzing how the natural system works, but to simplify matters we use the usual techniques of scientific reductionism and make the natural system much simpler than usual. Then we take a subset of the natural system and simulate or mimic it. Have we captured the right parts?

More than just capturing the relationships between the parts correctly, such a reductionist approach is at risk of opting for efficiency over resilience or even sacrificing both efficiency and resilience. That is, such an approach could confuse a Rube Goldberg machine that mimics Nature for the real thing. One of the hallmarks of a Rube Goldberg machine is not only its complexity but also its fragility — its lack of resilience. If even one step along the way fails, the whole system fails to achieve its objective, and is not self-repairing.

Thus there might be an important distinction between inherent complexity and apparent complexity. That is, if biomimicry is an important approach to solving problems to meet human needs in a more sane way, we need to be able to differentiate between the Rube Goldberg machine and a bona fide web of life. While Nature might look like a Rube Goldberg machine, it has inherent complexity.

I think this distinction between inherent and apparent complexity arises is many contexts. Consider the subfield of mathematical topology known as knot theory, which is about the study of, well, knots. A circular piece of string might be of low apparent and inherent complexity — the “unknot”, which is just an open loop. Take that string, jumble it in your pocket, and take it out and lay it flat on a piece of paper. You can write labels for crossings that you see using dowker codes, and may arrive at the conclusion that the knot is complex — that it has many crossings (that, presumably, could be hard to untangle). However if you haven’t actually changed the loop of string in any way, and if you were to hold it in just the right position, it’d be clear that all you have is the unknot — that the inherent complexity is low despite high apparent complexity. In this context inherent complexity is captured in the concept of crossing numbers.

When we build a complex system using biomimicry — say the construction of a watercourse, selection of plants in a fruit-tree guild, design of a composting system intended to prevent phosphate loss, or any number of others — is the inherent complexity high or just the apparent complexity? How can we tell? Perhaps one easy way to tell is to break the system. If I identify, say, 10 places I could break the system, and break it in those spots, what happens? Does the system route around the failure, or does it fail catastrophically due to my actions? If a leaf is decomposing and there are no appropriate fungi present, bacteria will get the job done, and vice versa; if neither are present, something else will take over. Only in degraded ecosystems — ones that have low inherent complexity — will decomposition not take place at all.

Perhaps then we should evaluate our systems not only by whether they mimic Nature well in the ways that they function but also how well they mimic Nature in the ways that they don’t.